Company Description Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. In publishing the best books in every genre and subject for all ages, we are committed to quality, excellence in execution, and innovation throughout the entire publishing process: editorial, design, marketing, publicity, sales, production, and distribution. Our vibrant and diverse international community of nearly 300 publishing brands and imprints include Ballantine Bantam Dell, Berkley, Clarkson Potter, Crown, DK, Doubleday, Dutton, Grosset & Dunlap, Little Golden Books, Knopf, Modern Library, Pantheon, Penguin Books, Penguin Press, Penguin Random House Audio, Penguin Young Readers, Portfolio, Puffin, Putnam, Random House, Random House Children's Books, Riverhead, Ten Speed Press, Viking, and Vintage, among others. More information can be found at Penguin Random House values the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status. Job Description Penguin Random House publishes more of the books people love than anyone else in the world and the Data Science team helps those books find their readers: recommendation systems that surface the right book for the right person, forecasting models that guide print runs and marketing spend, and AI-powered tools that support our publishing teams. We're hiring a Senior AI Solutions Engineer to build the systems behind this next wave of AI work for improving operations: agentic applications, LLM-powered services, and the interfaces (e.g. MCP servers) that connect AI models and assistants to our internal data and tools. You'll work at the intersection of a world-class publishing business and the modern AI stack, and you'll own what you build all the way to production. Specific responsibilities include: Design, build, and operate LLM-powered applications and services (e.g. agentic workflows, retrieval/RAG systems, classification pipelines) over our catalog, sales, and operational data Stand up and maintain MCP servers and tool integrations that connect AI models and assistants to our internal data and systems safely and reliably Own services end-to-end: architecture, implementation, deployment, evaluation, and monitoring in our AWS/Databricks environment Evaluate emerging AI tooling and patterns (agent frameworks, MCP, evaluation harnesses, new model capabilities), run structured pilots, and lead adoption of what works Raise the team's AI engineering capability: run working sessions and internal demos, pair program with scientists, and build internal tools to help accelerate AI usage across the team. Qualifications 3+ years building and shipping production-quality software, including hands-on work with machine learning or AI systems that include the following preferred qualifications: Experience standing up MCP servers or comparable tool-integration layers for AI assistants Experience with cloud ML platforms (AWS, Databricks), model APIs (Bedrock, Anthropic, OpenAI), and vector databases Advanced degree (MS/PhD) in computer science, machine learning, or a related quantitative field Experience applying AI/ML to commercial problems such as demand forecasting, pricing, sales and marketing optimization, recommendation, or search Background in media, publishing, or other content-rich domains Demonstrated fluency with the current LLM stack: retrieval-augmented generation, embeddings, prompt engineering, agentic patterns, and rigorous evaluation of generative systems Strong Python engineering skills with experience in version control, testing, and CI Self-motivated, with strong communication skills and a demonstrated ability to teach and level up teammates. Additional Information The salary range for this position is $180,000 to $220,000. All positions are currently eligible for annual profit award or bonus, subject to Company results. Applications for this role will be accepted through October 8, 2026 or until the role is filled. We encourage you to apply early, as we review applications on a rolling basis. For this position a complete application should include your resume and cover letter, as both are required for consideration. Before applying for any role at Penguin Random House, we recommend you review ou r applicant resources page and our FAQs page. Penguin Random House job postings include a good faith compensation range for each open position. The salary range listed is specific to each particular open position and takes into account various factors including the specifics of the individual role, and candidate's relevant experience and qualifications. Full-time employees are eligible for our comprehensive benefits program. Our range of benefits include, but are not limited to, Medical/Prescription drug insurance, Dental, Vision, Health Care/Dependent Care Flexible Spending Account, Health Savings Account, Pre-Tax and Roth 401(k), Short and Long-Term Disability Insurance, Life/AD&D Insurance, Commuter Benefits, Student Loan Repayment Program, Educational Assistance & generous paid time off. All your information will be kept confidential according to EEO guidelines. Disclosure requirements pertaining to the collection of your personal data: Responsible for processing the information provided in your application is the company specified in the job advertisement, with its registered office as indicated. The company processes your data for the purpose of establishing an employment relationship on the basis of Art. 6 (1) b GDPR / Section 26 (1) sentence 1 BDSG. The retention period for your data is determined by the statutory time limits applicable in the respective country, beginning upon completion of the recruitment process. You can find these here. You can contact the company's Data Protection Officer at the above-mentioned postal address. Further information on data protection and your rights can be found here. We value the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, age, genetic information, or pregnancy. All your information will be kept confidential according to EEO guidelines. Recruiting-Platform powered by SmartRecruiters .
09/24/2026
Full time
Company Description Penguin Random House is the leading adult and children's publishing house in North America, the United Kingdom and many other regions around the world. In publishing the best books in every genre and subject for all ages, we are committed to quality, excellence in execution, and innovation throughout the entire publishing process: editorial, design, marketing, publicity, sales, production, and distribution. Our vibrant and diverse international community of nearly 300 publishing brands and imprints include Ballantine Bantam Dell, Berkley, Clarkson Potter, Crown, DK, Doubleday, Dutton, Grosset & Dunlap, Little Golden Books, Knopf, Modern Library, Pantheon, Penguin Books, Penguin Press, Penguin Random House Audio, Penguin Young Readers, Portfolio, Puffin, Putnam, Random House, Random House Children's Books, Riverhead, Ten Speed Press, Viking, and Vintage, among others. More information can be found at Penguin Random House values the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status. Job Description Penguin Random House publishes more of the books people love than anyone else in the world and the Data Science team helps those books find their readers: recommendation systems that surface the right book for the right person, forecasting models that guide print runs and marketing spend, and AI-powered tools that support our publishing teams. We're hiring a Senior AI Solutions Engineer to build the systems behind this next wave of AI work for improving operations: agentic applications, LLM-powered services, and the interfaces (e.g. MCP servers) that connect AI models and assistants to our internal data and tools. You'll work at the intersection of a world-class publishing business and the modern AI stack, and you'll own what you build all the way to production. Specific responsibilities include: Design, build, and operate LLM-powered applications and services (e.g. agentic workflows, retrieval/RAG systems, classification pipelines) over our catalog, sales, and operational data Stand up and maintain MCP servers and tool integrations that connect AI models and assistants to our internal data and systems safely and reliably Own services end-to-end: architecture, implementation, deployment, evaluation, and monitoring in our AWS/Databricks environment Evaluate emerging AI tooling and patterns (agent frameworks, MCP, evaluation harnesses, new model capabilities), run structured pilots, and lead adoption of what works Raise the team's AI engineering capability: run working sessions and internal demos, pair program with scientists, and build internal tools to help accelerate AI usage across the team. Qualifications 3+ years building and shipping production-quality software, including hands-on work with machine learning or AI systems that include the following preferred qualifications: Experience standing up MCP servers or comparable tool-integration layers for AI assistants Experience with cloud ML platforms (AWS, Databricks), model APIs (Bedrock, Anthropic, OpenAI), and vector databases Advanced degree (MS/PhD) in computer science, machine learning, or a related quantitative field Experience applying AI/ML to commercial problems such as demand forecasting, pricing, sales and marketing optimization, recommendation, or search Background in media, publishing, or other content-rich domains Demonstrated fluency with the current LLM stack: retrieval-augmented generation, embeddings, prompt engineering, agentic patterns, and rigorous evaluation of generative systems Strong Python engineering skills with experience in version control, testing, and CI Self-motivated, with strong communication skills and a demonstrated ability to teach and level up teammates. Additional Information The salary range for this position is $180,000 to $220,000. All positions are currently eligible for annual profit award or bonus, subject to Company results. Applications for this role will be accepted through October 8, 2026 or until the role is filled. We encourage you to apply early, as we review applications on a rolling basis. For this position a complete application should include your resume and cover letter, as both are required for consideration. Before applying for any role at Penguin Random House, we recommend you review ou r applicant resources page and our FAQs page. Penguin Random House job postings include a good faith compensation range for each open position. The salary range listed is specific to each particular open position and takes into account various factors including the specifics of the individual role, and candidate's relevant experience and qualifications. Full-time employees are eligible for our comprehensive benefits program. Our range of benefits include, but are not limited to, Medical/Prescription drug insurance, Dental, Vision, Health Care/Dependent Care Flexible Spending Account, Health Savings Account, Pre-Tax and Roth 401(k), Short and Long-Term Disability Insurance, Life/AD&D Insurance, Commuter Benefits, Student Loan Repayment Program, Educational Assistance & generous paid time off. All your information will be kept confidential according to EEO guidelines. Disclosure requirements pertaining to the collection of your personal data: Responsible for processing the information provided in your application is the company specified in the job advertisement, with its registered office as indicated. The company processes your data for the purpose of establishing an employment relationship on the basis of Art. 6 (1) b GDPR / Section 26 (1) sentence 1 BDSG. The retention period for your data is determined by the statutory time limits applicable in the respective country, beginning upon completion of the recruitment process. You can find these here. You can contact the company's Data Protection Officer at the above-mentioned postal address. Further information on data protection and your rights can be found here. We value the array of talents and perspectives that a diverse workforce brings. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, age, genetic information, or pregnancy. All your information will be kept confidential according to EEO guidelines. Recruiting-Platform powered by SmartRecruiters .
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
09/24/2026
Full time
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
09/24/2026
Full time
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
09/24/2026
Full time
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
09/24/2026
Full time
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
09/24/2026
Full time
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
09/24/2026
Full time
At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity The Talent Advanced Analytics Lead is responsible for shaping and delivering the organization's next-generation Talent Intelligence and Advanced Analytics strategy. This role combines executive leadership advisory, advanced analytics, AI innovation, talent intelligence, and data product delivery to enable leaders to make faster, more informed decisions to unlock value and drive business impact. The role serves as a strategic advisor to global Talent, Function, Service Line, and Sector leaders by transforming talent, business, operational, and external market data into actionable intelligence. The individual will lead the development of scalable analytics products, AI-powered insights, and agentic solutions that enhance planning, skills intelligence, talent mobility, employee experience, productivity, and organizational effectiveness. Essential Functions: Talent Intelligence Strategy & Executive Advisory Partner with Global Talent Leadership, Function Talent Leaders, Service Line Leaders, and Planning leaders to define and execute the Talent Intelligence strategy. Act as a trusted advisor to executive stakeholders, translating complex workforce trends into strategic recommendations and actionable decisions. Drive data-informed decision making across planning, skills transformation, workforce evolution, talent acquisition, retention, learning, talent mobility, and succession planning, etc. Deliver executive-ready narratives that combine quantitative insights with business context and future workforce implications. Influence enterprise talent priorities through predictive and prescriptive analytics. Advanced Analytics & AI Solutions Lead the development of advanced analytics models to identify workforce risks, forecast talent demand, predict workforce trends, and uncover opportunities to improve organizational performance. Design and deploy AI-powered talent intelligence solutions using machine learning, Generative AI, natural language processing, knowledge graphs, and predictive modelling techniques. Establish scalable approaches for skills intelligence, workforce segmentation, talent forecasting, organizational network analysis, and workforce optimization. Define methodologies that combine internal talent data with external labour market intelligence and economic indicators. Continuously evaluate emerging technologies and analytics techniques to advance talent decision science capabilities. Generative AI, Copilot & Agentic Solutions Lead development of AI-enabled experiences using Data Bricks, Microsoft Fabric, Power BI, Microsoft Copilot, Copilot Studio, Azure AI, enterprise GenAI platforms and machine learning, and intelligent automation capabilities. Design and implement intelligent agents that automate talent insights generation, workforce analytics, executive insights, and decision support processes. Build conversational analytics experiences that enable leaders to interact with talent data through natural language. Establish governance, explainability, responsible AI, and adoption practices for AI-powered talent solutions. Partner with technology teams to integrate agentic workflows into Talent operating models and business processes. Drive experimentation and innovation through AI use cases that unlock measurable business value. Data Products & Platform Leadership Own the vision, roadmap, and lifecycle management of Talent analytics products and self-service insight solutions. Lead development of enterprise Talent data products designed for broad organizational consumption. Establish product management disciplines, user-centric design practices, and adoption strategies across Talent Intelligence initiatives. Drive the transition from static reporting toward intelligent, scalable, reusable analytics products. Identify opportunities to industrialize analytics capabilities and increase insight accessibility across stakeholder groups. Enable scalable analytics architecture supporting structured and unstructured talent data. Collaborate with Data Engineering and Technology teams to optimize data quality, governance, lineage, accessibility, and security. Drive modernization of the talent analytics ecosystem through cloud-native analytics capabilities. Insights, Storytelling & Executive Communications Transform analytical outputs into compelling executive narratives and strategic workforce recommendations. Create executive dashboards and insight products that simplify complex workforce information. Develop thought leadership that shapes future Talent Intelligence capabilities and workforce decision-making practices. Present findings confidently to executive talent leaders and senior business stakeholders. Drive adoption of analytics by making insights easily understandable, relevant, and actionable. Leadership & Capability Development Lead and develop a high-performing team of data scientists, workforce strategists, analytics consultants, AI practitioners, and product managers. Establish talent intelligence standards, methodologies, and governance frameworks. Foster a culture of innovation, experimentation, continuous learning, and responsible AI usage. Build organizational capabilities in analytics, AI literacy, data storytelling, and product thinking. Manage delivery across global, offshore, vendor, and managed-service teams where applicable. Analytical/Decision Making Responsibilities: Determine strategic priorities for Talent Intelligence and Advanced Analytics programs. Prioritize investments and resource allocation across analytics, AI, and data product portfolios. Define and monitor key workforce intelligence metrics and success measures. Evaluate emerging workforce trends, technologies, and market developments to influence strategic direction. Balance innovation investments with operational scalability, governance, and business value realization. Ensure responsible and ethical use of workforce data and AI solutions. Knowledge and Skills Requirements: Strategic & Business Skills Deep understanding of Talent Intelligence, Planning, Talent Analytics, Workforce Evolution and Talent Strategy. Strong consulting, stakeholder management, and executive influence capabilities. Ability to align talent analytics outcomes with broader business objectives. Strong commercial acumen and understanding of organizational transformation. Analytics & Data Science Skills Advanced statistical analysis and predictive modelling, Machine Learning and AI solution design, Experimental design and causal inference methodologies, Skills intelligence and talent marketplace analytics, Expertise in data storytelling and executive reporting. AI & Emerging Technology Skills Generative AI solutions design and implementation, Microsoft Copilot ecosystem expertise, Copilot Studio and conversational AI development, Agentic AI architecture and orchestration, Retrieval-Augmented Generation (RAG) patterns, Prompt engineering and AI governance, Responsible AI and model explainability, Knowledge management and semantic search solutions. Data & Technology Skills Data Bricks, Microsoft Fabric, Power BI and advanced visualization. SQL and advanced data modelling. Microsoft Copilot, Copilot Studio, Azure AI, Enterprise GenAI platforms and Machine Learning Python and R, Modern cloud analytics architectures. API and data integration concepts, Data governance and metadata management. Leadership Competencies Executive presence, Strategic thinking, Innovation mindset, Change leadership. Product-centric thinking, Collaboration across global teams, Enterprise influence and stakeholder engagement. Ability to cope with ambiguity; to drive change and performance outcomes in a complex and agile environment. Supervision Responsibilities: Work closely with the Leads across Global Talent and wider Talent Functions to ensure the provision of services that support business and functional delivery. Lead / manage a team of expert data analytics specialists responsible for functional execution, also build skills and capabilities of the team. Develop AI capabilities, define key AI competencies for the team, and ensure provision of learning to advance skills Independently maintain and leverage (when appropriate) an internal network, including effective partnerships with senior stakeholders, across EY practices / functions that will enable personal effectiveness in the position. Other Requirements: Due to global nature of the role; travel and willingness to work alternative hours will be required. Due to global nature of the role; English language skills - excellent written and verbal communication will be required. Job Requirements: Education: Bachelor's degree in data science, Analytics, Statistics, Computer Science, Economics, Business Analytics, Organizational Psychology, Industrial Engineering, Human Resources, or related discipline. . click apply for full job details
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
09/24/2026
Full time
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Auth0 Team Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers. We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier-Ø global service to deliver convenience, privacy, and security so customers can focus on innovation. This team focuses on providing tenant-level protections to our customers, at scale. From bot detection to brute-force to suspicious IP throttling and beyond, this team often provides the first line of defense for Auth0 customers. At Okta, we're building the next generation of authentication for the GenAI era. We're looking for a Senior Software Engineer to join the AI Agentic Experience team at Auth0. This role is pivotal in extending and complementing our Auth for GenAI offering by building the infrastructure, tooling, and developer experiences that empower both human developers and AI agents to build secure, intelligent applications. Auth0 Emerging Tech is the Engineering organization where we take care of the hottest technology out there: we ship fast, we don't break things. We are a dynamic and collaborative distributed and diverse team. We value ownership, learning and innovation. This is an ideal role for an engineer who enjoys building for other engineers, working across stacks, and shaping the future of AI enablement in production systems. You'll collaborate across engineering, product, and security teams to drive meaningful improvements in developer tooling, agent authentication, orchestration frameworks, and real-world demos. What you will be doing: Design and Build Developer Tooling that helps developers secure and manage infrastructure like MCP servers Build Demo Applications that showcase secure, identity-powered AI use cases in real-world environments Contribute to Open Source Projects , both within Auth0 and across the broader AI + identity ecosystem Write and Maintain High-Quality Documentation including API references, quickstarts, and best practices for both developers and AI-native tooling (e.g., llm.txt) Drive Integration with Emerging AI Frameworks by creating adapters, utilities, and interfaces for agent runtimes and orchestration layers Collaborate with Design, Product, and Security teams to align on developer needs, roadmap direction, and compliance requirements Mentor and Support Other Engineers , setting strong examples in code quality, testing practices, and architectural thinking Influence Engineering Standards by leading design discussions and contributing to team-wide architectural decisions Ensure Resilience and Security of systems involved in agent-to-agent or model-to-service communication You Might Be a Good Fit If You 5+ years of experience in software engineering with a proven track record in building tools, frameworks, or platforms for other developers Proficiency in JavaScript/TypeScript, Golang and/or Python , and the ability to move fluidly between front-end and back-end contexts Experience working with LLM APIs , agent runtimes, orchestration layers, or prompt pipelines Familiarity with authentication and authorization systems , especially standards like OAuth2, OIDC, and JWT Demonstrated experience leading architecture and design efforts for scalable, production-grade systems Comfort contributing to and maintaining open source projects and engaging with developer communities A passion for documentation as part of the developer experience-not just writing code, but making it understandable and usable Ability to thrive in highly collaborative environments with cross-functional stakeholders Technologies You May Work With Languages : JavaScript, TypeScript, Python Frameworks : React, Next.js, FastAPI AI Ecosystem : Model APIs, orchestration runtimes, prompt management systems, agent toolkits Auth0 Stack : Token Vault, Async Authorization, Fine-Grained Authorization (FGA) P23579_ Below is the annual base salary range for candidates located in San Francisco Bay Area. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in the San Francisco Bay area is between: $159,000-$239,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
09/24/2026
Full time
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Auth0 Team Auth0 is an easy-to-implement authentication and authorization platform designed by developers for developers. We make access to applications safe, secure, and seamless for the more than 100 million daily logins around the world. Our modern approach to identity enables this Tier-Ø global service to deliver convenience, privacy, and security so customers can focus on innovation. This team focuses on providing tenant-level protections to our customers, at scale. From bot detection to brute-force to suspicious IP throttling and beyond, this team often provides the first line of defense for Auth0 customers. At Okta, we're building the next generation of authentication for the GenAI era. We're looking for a Senior Software Engineer to join the AI Agentic Experience team at Auth0. This role is pivotal in extending and complementing our Auth for GenAI offering by building the infrastructure, tooling, and developer experiences that empower both human developers and AI agents to build secure, intelligent applications. Auth0 Emerging Tech is the Engineering organization where we take care of the hottest technology out there: we ship fast, we don't break things. We are a dynamic and collaborative distributed and diverse team. We value ownership, learning and innovation. This is an ideal role for an engineer who enjoys building for other engineers, working across stacks, and shaping the future of AI enablement in production systems. You'll collaborate across engineering, product, and security teams to drive meaningful improvements in developer tooling, agent authentication, orchestration frameworks, and real-world demos. What you will be doing: Design and Build Developer Tooling that helps developers secure and manage infrastructure like MCP servers Build Demo Applications that showcase secure, identity-powered AI use cases in real-world environments Contribute to Open Source Projects , both within Auth0 and across the broader AI + identity ecosystem Write and Maintain High-Quality Documentation including API references, quickstarts, and best practices for both developers and AI-native tooling (e.g., llm.txt) Drive Integration with Emerging AI Frameworks by creating adapters, utilities, and interfaces for agent runtimes and orchestration layers Collaborate with Design, Product, and Security teams to align on developer needs, roadmap direction, and compliance requirements Mentor and Support Other Engineers , setting strong examples in code quality, testing practices, and architectural thinking Influence Engineering Standards by leading design discussions and contributing to team-wide architectural decisions Ensure Resilience and Security of systems involved in agent-to-agent or model-to-service communication You Might Be a Good Fit If You 5+ years of experience in software engineering with a proven track record in building tools, frameworks, or platforms for other developers Proficiency in JavaScript/TypeScript, Golang and/or Python , and the ability to move fluidly between front-end and back-end contexts Experience working with LLM APIs , agent runtimes, orchestration layers, or prompt pipelines Familiarity with authentication and authorization systems , especially standards like OAuth2, OIDC, and JWT Demonstrated experience leading architecture and design efforts for scalable, production-grade systems Comfort contributing to and maintaining open source projects and engaging with developer communities A passion for documentation as part of the developer experience-not just writing code, but making it understandable and usable Ability to thrive in highly collaborative environments with cross-functional stakeholders Technologies You May Work With Languages : JavaScript, TypeScript, Python Frameworks : React, Next.js, FastAPI AI Ecosystem : Model APIs, orchestration runtimes, prompt management systems, agent toolkits Auth0 Stack : Token Vault, Async Authorization, Fine-Grained Authorization (FGA) P23579_ Below is the annual base salary range for candidates located in San Francisco Bay Area. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in the San Francisco Bay area is between: $159,000-$239,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
09/24/2026
Full time
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
09/24/2026
Full time
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
09/24/2026
Full time
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Infrastructure Platform and Shared Services Team Okta authenticates, authorizes and provisions millions of users a day. The service is hosted on Amazon Web Services (AWS) across multiple availability zones and geographically separated regions. The service is designed for high throughput and 99.999 availability. We're looking for a technical leader to help us continue to scale the service with great people and reliable, cost-effective, and efficient infrastructure, processes, and tooling. As the Sr. Manager of Infrastructure Platform and Shared Services, you will oversee multiple teams focused on Edge networking, K8s platform, Observability, automation platform & tooling. What you'll be doing Lead the Infra platform and shared services org and various initiatives across SRE & Infrastructure organization. Build a world-class observability platform and monitoring capabilities enabled with self-service Accelerate the velocity of SRE and product engineering by developing robust platforms, powerful tooling, and intuitive self-service capabilities. Own the design and operation of scalable, self-service Cloud infrastructure platforms (e.g. Observability Platform, SRE Productivity, deployments, and Edge Infrastructure) Lead, mentor, and grow a high-performing team of engineers and managers across SRE and infrastructure shared services domains. Perform engineering design evaluations and ensure the completion of projects within resource, budget, and scheduling constraints. Improve SDLC processes for Cloud infrastructure as a code, including the maturity of product deployements, change and release management Manage service and business expectations and prioritize resource allocation Maintain a deep knowledge of industry best practices, evolving trends, and technologies What you'll bring to the role 6+ years of experience in technical leadership & people management 3+ years of experience running large-scale infrastructure platforms supporting a SaaS/Cloud service in a public Cloud, preferably AWS. Experience supporting a multi-Cloud environment will be a plus. Strong expertise in cloud-native architectures, Edge infrastructure (WAF, ALB, NLB, Apache, Nginx), IaC (Terraform), Splunk, Grafana and CI/CD pipelines. Strong background and hands-on experience in SRE automation& tooling Deep experience with building and operating observability platforms and monitoring tools (Grafana, Splunk, APM etc.) in a large scale environment. Demonstrated ability to lead cross-functional teams and manage large-scale programs Effective verbal, written communication and interpersonal skills Computer Science Degree or related degree or equivalent experience Additional requirements: This position requires the ability to access federal environments and/or have access to protected federal data. As a condition of employment for this position, the successful candidate must be able to submit documentation establishing the U.S. Person status (e.g. a U.S. Citizen, National, Lawful Permanent Resident, Refugee, or Asylee. 22 CFR 120.15) upon hire. P8841_ Below is the annual base salary range for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York and Washington. Your actual base salary will depend on factors such as your skills, qualifications, experience, and work location. In addition, Okta offers equity (where applicable), bonus, and benefits, including health, dental and vision insurance, 401(k), flexible spending account, and paid leave (including PTO and parental leave) in accordance with our applicable plans and policies. To learn more about our Total Rewards program please visit: The annual base salary range for this position for candidates located in California (excluding San Francisco Bay Area), Colorado, Illinois, New York, and Washington is between: $232,000-$319,000 USD The Okta Experience Supporting Your Well-Being Driving Social Impact Developing Talent and Fostering Connection + Community We are intentional about connection. Our global community, spanning over 20 offices worldwide, is united by a drive to innovate. Your journey begins with an immersive, in-person onboarding experience designed to accelerate your impact and connect you to our mission and team from day one. Okta is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, marital status, age, physical or mental disability, or status as a protected veteran. We also consider for employment qualified applicants with arrest and convictions records, consistent with applicable laws. If reasonable accommodation is needed to complete any part of the job application, interview process, or onboarding please use this Form to request an accommodation. Notice for New York City Applicants & Employees: Okta may use Automated Employment Decision Tools (AEDT), as defined by New York City Local Law 144, that use artificial intelligence, machine learning, or other automated processes to assist in our recruitment and hiring process. In accordance with NYC Local Law 144, if you are an applicant or employee residing in New York City, please click here to view our full NYC AEDT Notice.
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI C3 AI is looking for Senior Software Engineers to join the rapidly growing Data org within the Platform Engineering department. Successful candidates will get the opportunity to work on high-value technologies at the intersection of large-scale distributed systems, data infrastructure, and machine learning. You will design, develop, and maintain various features in a highly scalable and extensible AI/ML platform for large-scale applications, involving data science, distributed systems, and multi-cloud strategy. You will be given opportunities to take ownership of components, collaborate to drive technical direction, and work on interesting, impactful projects. Join us in building the next-generation AI/ML platform at petabyte level scale that powers some of the world's largest companies in Energy, Financial Services, Utilities, Health Care, Aerospace, Defense, etc. Accelerate your career in the leading enterprise AI company that is in a hyper-growth trajectory. Responsibilities: Design and develop infrastructure and services to enable data pipelines for petabyte level scale and more. Design and develop abstractions over datastores such as Cassandra, PostgreSQL, Snowflake, etc. Design and develop file system abstractions over AWS S3, Azure Blobs, HDFS, etc. Design and develop connectors to various external data stores. Design and develop distributed system components for stream processing, queueing, batch processing, analytics engines, etc. Develop and maintain industry-leading, high-performance APIs for AL/ML applications. Develop and maintain features for distributed computations over large-scale data for ML workflows. Design and develop ML-specific data-systems such as feature stores and behavioral frameworks such as recommendation engines. Design and develop integrations with distributed computing technologies such as Apache Spark, Ray, etc. for data exploration and ML workload orchestration. Design and develop integrations with data analysis libraries such as Pandas, Koalas, etc. Develop and production AI/ML models for failure prediction, data schema inferencing, etc. Work on frameworks for performance, scalability, and reliability tracking over different components of a highly extensible AI/ML platform. Work with architects, product managers, and software engineers across teams in a highly collaborative environment. Participate and provide insights in technical discussions. Write clean code following a test-driven methodology. Deliver commitments promptly following agile software development methodology. Qualifications: Bachelor of Science in Computer Science, Computer Engineering, or related fields. A minimum of 5 years of work experience in a fast-paced software company. Strong understanding of Computer Science fundamentals. High proficiency in coding with Java, C++, C#, or some other compiled language. Python would also be acceptable. Strong competency in object-oriented programming, data structures, algorithms, and software design patterns. Experience with version control systems such as Git. Experience with large-scale distributed systems. Experience with any public cloud platform (AWS, Azure, GCP). Some familiarity with distributed computing technologies (e.g., Hadoop, Spark, Kafka). Familiarity with managed versions of these technologies on public cloud platforms is also acceptable. Familiarity with technologies in the modern data science/analysis and engineering ecosystem (e.g., Pandas, Koalas). Good verbal and written technical communication ability to facilitate collaboration. Thrive in a fast-paced, dynamic environment and value end-to-end ownership of components. Intellectually curious and open to challenges. Preferred Qualifications: Advanced degree in engineering, sciences, or related field. Experience with Agile development methodology. Experience developing and working with REST and/or GraphQL APIs. Experience building scalable and reliable data pipelines. Experience with integration of data from multiple sources. Experience working with analytics and/or data processing engines. Experience developing distributed computation over large-scale data. Experience working with distributed computing frameworks (e.g., Hadoop, Spark, Kafka). Experience with data science/analysis libraries (e.g., Pandas, Koalas). Experience with task schedulers in distributed computing (e.g., Spark, Ray, Dask). Familiarity with machine learning workload orchestration in a distributed computing environment. Familiarity with workflow execution and/or optimization using DAGs, ideally for machine learning use-cases. Conceptual understanding of orchestration and resource provisioning systems (Kubernetes) C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. California Base Pay Range $145,000-$187,000 USD C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
09/24/2026
Full time
C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI C3 AI is looking for Senior Software Engineers to join the rapidly growing Data org within the Platform Engineering department. Successful candidates will get the opportunity to work on high-value technologies at the intersection of large-scale distributed systems, data infrastructure, and machine learning. You will design, develop, and maintain various features in a highly scalable and extensible AI/ML platform for large-scale applications, involving data science, distributed systems, and multi-cloud strategy. You will be given opportunities to take ownership of components, collaborate to drive technical direction, and work on interesting, impactful projects. Join us in building the next-generation AI/ML platform at petabyte level scale that powers some of the world's largest companies in Energy, Financial Services, Utilities, Health Care, Aerospace, Defense, etc. Accelerate your career in the leading enterprise AI company that is in a hyper-growth trajectory. Responsibilities: Design and develop infrastructure and services to enable data pipelines for petabyte level scale and more. Design and develop abstractions over datastores such as Cassandra, PostgreSQL, Snowflake, etc. Design and develop file system abstractions over AWS S3, Azure Blobs, HDFS, etc. Design and develop connectors to various external data stores. Design and develop distributed system components for stream processing, queueing, batch processing, analytics engines, etc. Develop and maintain industry-leading, high-performance APIs for AL/ML applications. Develop and maintain features for distributed computations over large-scale data for ML workflows. Design and develop ML-specific data-systems such as feature stores and behavioral frameworks such as recommendation engines. Design and develop integrations with distributed computing technologies such as Apache Spark, Ray, etc. for data exploration and ML workload orchestration. Design and develop integrations with data analysis libraries such as Pandas, Koalas, etc. Develop and production AI/ML models for failure prediction, data schema inferencing, etc. Work on frameworks for performance, scalability, and reliability tracking over different components of a highly extensible AI/ML platform. Work with architects, product managers, and software engineers across teams in a highly collaborative environment. Participate and provide insights in technical discussions. Write clean code following a test-driven methodology. Deliver commitments promptly following agile software development methodology. Qualifications: Bachelor of Science in Computer Science, Computer Engineering, or related fields. A minimum of 5 years of work experience in a fast-paced software company. Strong understanding of Computer Science fundamentals. High proficiency in coding with Java, C++, C#, or some other compiled language. Python would also be acceptable. Strong competency in object-oriented programming, data structures, algorithms, and software design patterns. Experience with version control systems such as Git. Experience with large-scale distributed systems. Experience with any public cloud platform (AWS, Azure, GCP). Some familiarity with distributed computing technologies (e.g., Hadoop, Spark, Kafka). Familiarity with managed versions of these technologies on public cloud platforms is also acceptable. Familiarity with technologies in the modern data science/analysis and engineering ecosystem (e.g., Pandas, Koalas). Good verbal and written technical communication ability to facilitate collaboration. Thrive in a fast-paced, dynamic environment and value end-to-end ownership of components. Intellectually curious and open to challenges. Preferred Qualifications: Advanced degree in engineering, sciences, or related field. Experience with Agile development methodology. Experience developing and working with REST and/or GraphQL APIs. Experience building scalable and reliable data pipelines. Experience with integration of data from multiple sources. Experience working with analytics and/or data processing engines. Experience developing distributed computation over large-scale data. Experience working with distributed computing frameworks (e.g., Hadoop, Spark, Kafka). Experience with data science/analysis libraries (e.g., Pandas, Koalas). Experience with task schedulers in distributed computing (e.g., Spark, Ray, Dask). Familiarity with machine learning workload orchestration in a distributed computing environment. Familiarity with workflow execution and/or optimization using DAGs, ideally for machine learning use-cases. Conceptual understanding of orchestration and resource provisioning systems (Kubernetes) C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. California Base Pay Range $145,000-$187,000 USD C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.
About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That's where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform , empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace-so teams can ship faster with confidence. We're a Series C company backed by top-tier investors,with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works. The Opportunity AI is rapidly transforming the world. Whether it's developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into various aspects of our daily lives. Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production. The Team Our Fullstack Engineering team builds both the highly scalable distributed services that power Arize's ML observability platform and the intuitive frontend applications that bring these capabilities to life. The team primarily works in TypeScript and Python to create seamless data visualization and monitoring experiences, with some services written in Go. We focus on delivering robust features that help clients interpret, visualize, and monitor their AI and ML models across the entire stack. You will be a part of the core team that drives product innovation at Arize. You will be challenged with understanding how some of the most impactful engineering teams are developing AI and LLM-powered applications, and how to build the right tools to enable them to do their best work. Our product solutions range from clean APIs that magically instrument applications, interactive playgrounds for prompt engineering and agent development, or scaling up real-time evaluation infrastructure to handle millions of annotations per second What You'll Do Write maintainable, scalable, and performant code across the stack primarily in Typescript and React with opportunities to work in Python and Go. Design and build APIs, and domain / object models specific to our customers' Machine Learning and LLM workflows. Design and build out performant and reusable react components that will be used throughout the application. Research and implement cutting-edge visualization & dimensionality reduction algorithms in a distributed environment. Collaborate with our product, design, and directly with customer engineering teams to enhance and expand our product offerings. Contribute to the build our own in-house AI Agents Participate in or lead architectural decisions for new and existing features in collaboration with product, design and our backend teams. Contribute to design & code reviews and technical documentation. What We're Looking For 5+ years of frontend experience working on external user-facing UI's - preferably in React and Typescript Previous experience debugging complex systems in a team environment. Enthusiasm and interest in the AI and LLM ecosystem, with a desire to learn and stay updated on emerging technologies. Previous work building and operating highly complex, high-volume SaaS platforms/systems. Strong sense of product ownership in order to push features over the line. Passion for creating beautiful UX design with the end user in mind. A good teammate, someone who sees supporting their team as a core part of the job Bonus Points, But Not Required Experience working with GraphQl or a comparable API technology. Experience working with ML, analytics, data science or data visualization products. Working knowledge of Machine Learning and/or Data Science. First-hand experience working with large language models (LLMs) or developing AI products. The estimated annual salary for this role is between $125,000 - $225,000, plus a competitive equity package. Actual compensation is determined based on a variety of job-related factors that may include transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefits package, including medical, dental, vision, a 401(k) plan, unlimited paid time off, a generous parental leave plan, and additional support for mental health and wellness. While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces. More About Arize Arize's mission is to make the world's AI work-and work for people. Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge-understanding whether AI is performing and how to improve it at scale. Learn more about what we're doing here: Diversity & Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI Culturally conscious events such as LGBTQ trivia during pride month We have an active Lady Arizers subgroup
09/24/2026
Full time
About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That's where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform , empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace-so teams can ship faster with confidence. We're a Series C company backed by top-tier investors,with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works. The Opportunity AI is rapidly transforming the world. Whether it's developing the next generation of human-level intelligence, enhancing voice assistants, or enabling researchers to analyze genetic markers at scale, AI is increasingly integrated into various aspects of our daily lives. Arize AI is the leading AI observability and evaluation platform, empowering AI engineers to build and deploy high-performing, reliable models. As the AI landscape shifts from traditional ML to generative AI and agentic systems, Arize ensures teams have the tools to monitor, troubleshoot, and improve AI in production. The Team Our Fullstack Engineering team builds both the highly scalable distributed services that power Arize's ML observability platform and the intuitive frontend applications that bring these capabilities to life. The team primarily works in TypeScript and Python to create seamless data visualization and monitoring experiences, with some services written in Go. We focus on delivering robust features that help clients interpret, visualize, and monitor their AI and ML models across the entire stack. You will be a part of the core team that drives product innovation at Arize. You will be challenged with understanding how some of the most impactful engineering teams are developing AI and LLM-powered applications, and how to build the right tools to enable them to do their best work. Our product solutions range from clean APIs that magically instrument applications, interactive playgrounds for prompt engineering and agent development, or scaling up real-time evaluation infrastructure to handle millions of annotations per second What You'll Do Write maintainable, scalable, and performant code across the stack primarily in Typescript and React with opportunities to work in Python and Go. Design and build APIs, and domain / object models specific to our customers' Machine Learning and LLM workflows. Design and build out performant and reusable react components that will be used throughout the application. Research and implement cutting-edge visualization & dimensionality reduction algorithms in a distributed environment. Collaborate with our product, design, and directly with customer engineering teams to enhance and expand our product offerings. Contribute to the build our own in-house AI Agents Participate in or lead architectural decisions for new and existing features in collaboration with product, design and our backend teams. Contribute to design & code reviews and technical documentation. What We're Looking For 5+ years of frontend experience working on external user-facing UI's - preferably in React and Typescript Previous experience debugging complex systems in a team environment. Enthusiasm and interest in the AI and LLM ecosystem, with a desire to learn and stay updated on emerging technologies. Previous work building and operating highly complex, high-volume SaaS platforms/systems. Strong sense of product ownership in order to push features over the line. Passion for creating beautiful UX design with the end user in mind. A good teammate, someone who sees supporting their team as a core part of the job Bonus Points, But Not Required Experience working with GraphQl or a comparable API technology. Experience working with ML, analytics, data science or data visualization products. Working knowledge of Machine Learning and/or Data Science. First-hand experience working with large language models (LLMs) or developing AI products. The estimated annual salary for this role is between $125,000 - $225,000, plus a competitive equity package. Actual compensation is determined based on a variety of job-related factors that may include transferable work experience, skill sets, and qualifications. Total compensation also includes a comprehensive benefits package, including medical, dental, vision, a 401(k) plan, unlimited paid time off, a generous parental leave plan, and additional support for mental health and wellness. While we are a remote-first company, we have opened offices in New York City and the San Francisco Bay Area, as an option for those in those cities who wish to work in-person. For all other employees, there is a WFH monthly stipend to pay for co-working spaces. More About Arize Arize's mission is to make the world's AI work-and work for people. Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge-understanding whether AI is performing and how to improve it at scale. Learn more about what we're doing here: Diversity & Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI Culturally conscious events such as LGBTQ trivia during pride month We have an active Lady Arizers subgroup
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
09/24/2026
Full time
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
Job Description Job Description As a Senior Network Security Engineer at Penumbra, you will play a critical role in determining the company's long term goals. You will be a key member of the Information Security and Compliance team. This is a highly technical, hands-on role. The Sr. Network Engineer will collaborate with Security, IT, Manufacturing, and Engineering teams and be responsible for engineering solutions and supporting operational activities across a hybrid cloud environment. The role responsibilities include ensuring compliance with legal and regulatory requirements and maintaining company security policies, standards, and industry's best practices. What You'll Work On • Ensure the network security of on-premises and cloud-based systems, networks, infrastructure, and services. • Enforce secure design standards and specifications for services, systems, and products. • Responsible for network security solutions, control designs, and enforcement across our environment. • Design and perform security assessments, configuration verification, configuration reporting, and other activities to validate control effectiveness. • Engage and share results of security audits with the Information Security and business partners to promote changes vital to improve risk posture. • Collaborate with cross-functional teams to develop and implement security measures supporting on-prem and cloud systems. • Develop roadmaps, standards, and documentation for technical solutions and existing configurations. Serve as the subject matter expert across the network security environment. • Respond to and lead, as appropriate, incident response activities for security incidents. • Collaborate with IT and line of business teams to integrate security into new and existing systems, processes, and initiatives. • Manage and configure security services, e.g., firewalls, intrusion detection/prevention systems, threat prevention technologies, VPNs, and other network security appliances. • Create and maintain documentation for security procedures, designs, and protocols, conduct security training and awareness for staff as appropriate to the role. • Stay current with emerging security threats and technologies in the security landscape. Ensure compliance with regulatory requirements and industry standards in the Company's environment. What You Contribute • A Bachelor's degree in computer science or related field with 10+ years of related experience, or equivalent combination of education and experience. • Master's degree preferred in Computer Science or Engineering with an emphasis in Computer Security or a related field • Highly analytical and results and process-oriented mindset strongly desired • 10+ years of hands-on design, enforcement and testing/validation of offensive security, defensive security, systems, and solutions engineering in a large enterprise • 5+ years of hands-on security experience with cloud platforms, i.e., Azure, AWS or Google Cloud Platform services, automation, or IaC • 5+ years of hands-on experience network security experience and expert-level knowledge on security technologies such as Palo Alto Firewalls, Cisco ISE, IPS, CASB, VPN management, SAML/OIDC NAC 802.1X, SIEM, SOAR, Radius/TACACS+, directory services • Proficient with network topologies, routing protocols, i.e., OSPF, BGP, ISIS, SDN, and tunneling technologies. • Proficient with diagramming and threat models, ability and competency to design and implement controls at scale based on risks • Proficient in conducting solutions architecture, security design reviews, passionate about security and privacy research, technologies, and methods. • Possess an understanding of past and emerging security exploits, threat actor motivations, and trends • Understanding security and compliance frameworks, security engineering, software delivery, and SDLC in a hybrid environment • Outstanding ethical standards and integrity. • Excellent communicator with strong oral, written, and interpersonal communication skills • High degree of accuracy and attention to detail • Proficiency with Microsoft Word, Excel, Visio, and PowerPoint • Excellent organizational skills with the ability to prioritize assignments while handling various projects simultaneously. Working Conditions General office environment. Willingness and ability to work on site. May have business travel up to 10%. Requires some lifting and moving of up to 10 pounds Must be able to move between buildings and floors. Must be able to remain stationary and use a computer or other standard office equipment, such as a printer or copy machine, for an extensive period of time each day. Must be able to read, prepare emails, and produce documents and spreadsheets. Must be able to move within the office and access file cabinets or supplies, as needed. Must be able to communicate and exchange accurate information with employees at all levels on a daily basis. Annual Base Salary Range: $146,000 - $220,000/ year We offer a competitive compensation package plus a benefits and equity program, when applicable. Individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. What We Offer • A collaborative teamwork environment where learning is constant, and performance is rewarded. • The opportunity to be part of the team that is revolutionizing the treatment of some of the world's most devastating diseases. • A generous benefits package for eligible employees that includes medical, dental, vision, life, AD&D, short and long-term disability insurance, 401(k) with employer match, paid parental leave, eleven paid company holidays per year, a minimum of fifteen days of accrued vacation per year, which increases with tenure, and paid sick time in compliance with applicable law(s). Penumbra, Inc., headquartered in Alameda, California, is a global healthcare company focused on innovative therapies. Penumbra designs, develops, manufactures, and markets novel products and has a broad portfolio that addresses challenging medical conditions in markets with significant unmet need. Penumbra sells its products to hospitals and healthcare providers primarily through its direct sales organization in the United States, most of Europe, Canada, and Australia, and through distributors in select international markets. The Penumbra logo is a trademark of Penumbra, Inc. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, military or veteran status, or any other characteristic protected by federal, state, or local laws. If you reside in the State of California, please also refer to Penumbra's Privacy Notice for California Residents. For additional information on Penumbra's commitment to being an equal opportunity employer, please see Penumbra's AAP Policy Statement.
09/24/2026
Full time
Job Description Job Description As a Senior Network Security Engineer at Penumbra, you will play a critical role in determining the company's long term goals. You will be a key member of the Information Security and Compliance team. This is a highly technical, hands-on role. The Sr. Network Engineer will collaborate with Security, IT, Manufacturing, and Engineering teams and be responsible for engineering solutions and supporting operational activities across a hybrid cloud environment. The role responsibilities include ensuring compliance with legal and regulatory requirements and maintaining company security policies, standards, and industry's best practices. What You'll Work On • Ensure the network security of on-premises and cloud-based systems, networks, infrastructure, and services. • Enforce secure design standards and specifications for services, systems, and products. • Responsible for network security solutions, control designs, and enforcement across our environment. • Design and perform security assessments, configuration verification, configuration reporting, and other activities to validate control effectiveness. • Engage and share results of security audits with the Information Security and business partners to promote changes vital to improve risk posture. • Collaborate with cross-functional teams to develop and implement security measures supporting on-prem and cloud systems. • Develop roadmaps, standards, and documentation for technical solutions and existing configurations. Serve as the subject matter expert across the network security environment. • Respond to and lead, as appropriate, incident response activities for security incidents. • Collaborate with IT and line of business teams to integrate security into new and existing systems, processes, and initiatives. • Manage and configure security services, e.g., firewalls, intrusion detection/prevention systems, threat prevention technologies, VPNs, and other network security appliances. • Create and maintain documentation for security procedures, designs, and protocols, conduct security training and awareness for staff as appropriate to the role. • Stay current with emerging security threats and technologies in the security landscape. Ensure compliance with regulatory requirements and industry standards in the Company's environment. What You Contribute • A Bachelor's degree in computer science or related field with 10+ years of related experience, or equivalent combination of education and experience. • Master's degree preferred in Computer Science or Engineering with an emphasis in Computer Security or a related field • Highly analytical and results and process-oriented mindset strongly desired • 10+ years of hands-on design, enforcement and testing/validation of offensive security, defensive security, systems, and solutions engineering in a large enterprise • 5+ years of hands-on security experience with cloud platforms, i.e., Azure, AWS or Google Cloud Platform services, automation, or IaC • 5+ years of hands-on experience network security experience and expert-level knowledge on security technologies such as Palo Alto Firewalls, Cisco ISE, IPS, CASB, VPN management, SAML/OIDC NAC 802.1X, SIEM, SOAR, Radius/TACACS+, directory services • Proficient with network topologies, routing protocols, i.e., OSPF, BGP, ISIS, SDN, and tunneling technologies. • Proficient with diagramming and threat models, ability and competency to design and implement controls at scale based on risks • Proficient in conducting solutions architecture, security design reviews, passionate about security and privacy research, technologies, and methods. • Possess an understanding of past and emerging security exploits, threat actor motivations, and trends • Understanding security and compliance frameworks, security engineering, software delivery, and SDLC in a hybrid environment • Outstanding ethical standards and integrity. • Excellent communicator with strong oral, written, and interpersonal communication skills • High degree of accuracy and attention to detail • Proficiency with Microsoft Word, Excel, Visio, and PowerPoint • Excellent organizational skills with the ability to prioritize assignments while handling various projects simultaneously. Working Conditions General office environment. Willingness and ability to work on site. May have business travel up to 10%. Requires some lifting and moving of up to 10 pounds Must be able to move between buildings and floors. Must be able to remain stationary and use a computer or other standard office equipment, such as a printer or copy machine, for an extensive period of time each day. Must be able to read, prepare emails, and produce documents and spreadsheets. Must be able to move within the office and access file cabinets or supplies, as needed. Must be able to communicate and exchange accurate information with employees at all levels on a daily basis. Annual Base Salary Range: $146,000 - $220,000/ year We offer a competitive compensation package plus a benefits and equity program, when applicable. Individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. What We Offer • A collaborative teamwork environment where learning is constant, and performance is rewarded. • The opportunity to be part of the team that is revolutionizing the treatment of some of the world's most devastating diseases. • A generous benefits package for eligible employees that includes medical, dental, vision, life, AD&D, short and long-term disability insurance, 401(k) with employer match, paid parental leave, eleven paid company holidays per year, a minimum of fifteen days of accrued vacation per year, which increases with tenure, and paid sick time in compliance with applicable law(s). Penumbra, Inc., headquartered in Alameda, California, is a global healthcare company focused on innovative therapies. Penumbra designs, develops, manufactures, and markets novel products and has a broad portfolio that addresses challenging medical conditions in markets with significant unmet need. Penumbra sells its products to hospitals and healthcare providers primarily through its direct sales organization in the United States, most of Europe, Canada, and Australia, and through distributors in select international markets. The Penumbra logo is a trademark of Penumbra, Inc. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, age, disability, military or veteran status, or any other characteristic protected by federal, state, or local laws. If you reside in the State of California, please also refer to Penumbra's Privacy Notice for California Residents. For additional information on Penumbra's commitment to being an equal opportunity employer, please see Penumbra's AAP Policy Statement.
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description As a discipline expert and technology leader, the Principal AI Engineer II will define and advance the strategy, architecture, and engineering practices required to develop, deploy, and scale artificial intelligence solutions across AbbVie. This role will investigate, identify, and implement state-of-the-art technology platforms that drive productivity and efficiency gains in own function and throughout multiple business areas. Technical leader acting at a group, department, and cross-functional levels. Responsible for managing the Data, Solutions, Business, and/or technology environments and tying them to the Enterprise Architecture and other architectures designs. Responsibilities: Define and advance AI engineering strategy, architecture, standards, and roadmaps aligned with AbbVie's business and technology objectives. Architect and build secure, scalable, reusable AI platforms, services, developer tools, and components that support enterprise adoption. Lead production-grade AI solutions from ideation and prototyping through development, testing, validation, deployment, monitoring, continuous improvement, and retirement. Integrate AI platforms with AWS services and enterprise data, software, security, identity, and infrastructure environments. Establish practices for evaluation, testing, versioning, release management, observability, performance monitoring, incident response, and operational support. Apply risk-based approaches to compliance, GxP, data integrity, privacy, cybersecurity, documentation, traceability, human oversight, and responsible AI. Partner with Quality, Regulatory, Legal, Privacy, Information Security, scientific, technical, and business stakeholders to deliver fit-for-purpose solutions. Serve as a trusted technical advisor, facilitate alignment, influence decisions without direct authority, and communicate complex tradeoffs and recommendations to technical and non-technical audiences. Evaluate emerging technologies, lead innovation and proof-of-concept efforts, and guide promising solutions into sustainable production capabilities. Mentor engineers, advance engineering maturity, promote knowledge sharing, and represent AbbVie in relevant technical communities and partner engagements. Qualifications Required Bachelor's degree with 9 years' experience, Master's degree with 8 years' experience, or PhD with 4 years' in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline. Demonstrated experience designing, deploying, and operating production-scale AI and machine learning systems. Strong experience in AI/platform engineering, including scalable platforms, reusable components, and production-grade AI solutions. Demonstrated experience designing, building, deploying, and supporting solutions using AWS systems and services. Strong software and cloud engineering practices, including secure design, automated testing, CI/CD, containerization, monitoring, and operational support. Experience working in a regulated environment, preferably pharmaceutical, biotechnology, healthcare, medical device, or life sciences. Experience supporting the full solution lifecycle, including feasibility, design, development, testing, validation, deployment, and ongoing operations. Strong understanding of risk management, validation, change control, data integrity, cybersecurity, privacy, documentation, and quality requirements. Demonstrated ability to manage complex stakeholders, influence technical and business decisions, and collaborate across organizational boundaries. Excellent communication skills with senior leaders, technical teams, scientific experts, business partners, and external collaborators. Demonstrated innovation and mentoring experience, including advancing engineering practices and delivering measurable impact. Preferred Experience with enterprise AI governance, responsible AI, model validation, human oversight, and AI lifecycle management. Experience with MLOps and production engineering, including model evaluation, APIs, microservices, CI/CD, observability, and infrastructure as code. Open-source contributions or technical thought leadership through publications, patents, or industry working groups. Experience leading cross-functional product development from feasibility through validation and production implementation. Enterprise AI or platform experience, including AWS architecture, governance, security, and integration with enterprise environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html
09/24/2026
Full time
Job Description Job Description Company Description About AbbVie AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on LinkedIn, Facebook, Instagram, X and YouTube. Job Description As a discipline expert and technology leader, the Principal AI Engineer II will define and advance the strategy, architecture, and engineering practices required to develop, deploy, and scale artificial intelligence solutions across AbbVie. This role will investigate, identify, and implement state-of-the-art technology platforms that drive productivity and efficiency gains in own function and throughout multiple business areas. Technical leader acting at a group, department, and cross-functional levels. Responsible for managing the Data, Solutions, Business, and/or technology environments and tying them to the Enterprise Architecture and other architectures designs. Responsibilities: Define and advance AI engineering strategy, architecture, standards, and roadmaps aligned with AbbVie's business and technology objectives. Architect and build secure, scalable, reusable AI platforms, services, developer tools, and components that support enterprise adoption. Lead production-grade AI solutions from ideation and prototyping through development, testing, validation, deployment, monitoring, continuous improvement, and retirement. Integrate AI platforms with AWS services and enterprise data, software, security, identity, and infrastructure environments. Establish practices for evaluation, testing, versioning, release management, observability, performance monitoring, incident response, and operational support. Apply risk-based approaches to compliance, GxP, data integrity, privacy, cybersecurity, documentation, traceability, human oversight, and responsible AI. Partner with Quality, Regulatory, Legal, Privacy, Information Security, scientific, technical, and business stakeholders to deliver fit-for-purpose solutions. Serve as a trusted technical advisor, facilitate alignment, influence decisions without direct authority, and communicate complex tradeoffs and recommendations to technical and non-technical audiences. Evaluate emerging technologies, lead innovation and proof-of-concept efforts, and guide promising solutions into sustainable production capabilities. Mentor engineers, advance engineering maturity, promote knowledge sharing, and represent AbbVie in relevant technical communities and partner engagements. Qualifications Required Bachelor's degree with 9 years' experience, Master's degree with 8 years' experience, or PhD with 4 years' in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related technical discipline. Demonstrated experience designing, deploying, and operating production-scale AI and machine learning systems. Strong experience in AI/platform engineering, including scalable platforms, reusable components, and production-grade AI solutions. Demonstrated experience designing, building, deploying, and supporting solutions using AWS systems and services. Strong software and cloud engineering practices, including secure design, automated testing, CI/CD, containerization, monitoring, and operational support. Experience working in a regulated environment, preferably pharmaceutical, biotechnology, healthcare, medical device, or life sciences. Experience supporting the full solution lifecycle, including feasibility, design, development, testing, validation, deployment, and ongoing operations. Strong understanding of risk management, validation, change control, data integrity, cybersecurity, privacy, documentation, and quality requirements. Demonstrated ability to manage complex stakeholders, influence technical and business decisions, and collaborate across organizational boundaries. Excellent communication skills with senior leaders, technical teams, scientific experts, business partners, and external collaborators. Demonstrated innovation and mentoring experience, including advancing engineering practices and delivering measurable impact. Preferred Experience with enterprise AI governance, responsible AI, model validation, human oversight, and AI lifecycle management. Experience with MLOps and production engineering, including model evaluation, APIs, microservices, CI/CD, observability, and infrastructure as code. Open-source contributions or technical thought leadership through publications, patents, or industry working groups. Experience leading cross-functional product development from feasibility through validation and production implementation. Enterprise AI or platform experience, including AWS architecture, governance, security, and integration with enterprise environments. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees. This job is eligible to participate in our long-term incentive programs. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law. AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. US & Puerto Rico only - to learn more, visit -us/equal-employment-opportunity-employer.html US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: -us/reasonable- accommodations.html
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in San Francisco, Bay Area. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
09/24/2026
Full time
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in San Francisco, Bay Area. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
09/23/2026
Full time
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
09/23/2026
Full time
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Product Security Engineer, AI & DevSecOps to embed security throughout our software development lifecycle, with a focus on AI-enabled products, cloud-native platforms, and DevSecOps practices. This is a hands-on technical role for a security-minded software developer who understands how applications are designed, written, deployed, and operated. You will partner directly with engineering, platform, architecture, and product teams to translate security requirements into practical guidance, reusable patterns, shared services, and automated controls that help teams deliver products faster and more securely. The ideal candidate combines hands-on software development experience with deep knowledge of application security, AI security, attack vectors, vulnerability remediation, and security automation. What You'll Do: Partner with development teams to incorporate security requirements throughout application design, development, testing, deployment, and operations Conduct security architecture reviews, threat modeling, secure design reviews, and assessments of applications, APIs, cloud services, and AI-enabled systems Write and review code to identify vulnerabilities, attack vectors, and opportunities to strengthen secure development practices Develop reusable security patterns, shared services, and automated guardrails that help engineering teams deliver products securely and efficiently Assess and secure AI, machine learning, generative AI, and large language model solutions, including the secure use of AI-assisted development tools Integrate automated security testing into CI/CD pipelines, including SAST, DAST, software composition analysis, secrets detection, container scanning, and infrastructure scanning Design security controls for cloud-native applications, containers, Kubernetes, serverless platforms, and infrastructure-as-code deployments Partner with engineering and cybersecurity teams to assess risk, remediate vulnerabilities, respond to security concerns, and promote a security-first engineering culture Basic Requirements: Degree in Computer Science, Information Security, Engineering, or a related technical field, or equivalent professional experience Typically requires 7 or more years of relevant experience in application security, product security, software development, security engineering, DevSecOps, or a related discipline Hands-on experience writing, reviewing, and deploying application code using TypeScript, Java, Ruby, Python, or comparable languages Strong understanding of application attack vectors, secure coding practices, software vulnerabilities, and modern application architectures Experience conducting threat modeling, security architecture reviews, secure design reviews, and vulnerability remediation Experience implementing DevSecOps practices and integrating automated security controls into CI/CD pipelines Experience securing AI/ML platforms, generative AI solutions, large language model applications, or AI-assisted development workflows Experience with cloud platforms, containers, Kubernetes, infrastructure-as-code, security automation, and application security testing tools Preferred Skills and Experience: Knowledge of AI security frameworks and controls, including the OWASP Top 10 for LLM Applications and the NIST AI Risk Management Framework Experience creating reusable security services, secure development patterns, engineering guardrails, or policy-as-code solutions Experience with CI/CD and infrastructure technologies such as GitHub Actions, Azure DevOps, GitLab, Jenkins, or Terraform Experience supporting frameworks such as SOC 2, HIPAA, SOX, NIST CSF, or ISO 27001 Ability to translate complex security requirements and technical risks into practical guidance for development teams Strong collaboration and influencing skills, with the ability to advance security without unnecessarily slowing product delivery McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role. Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) now or in the future. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $140,300 - $233,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!
