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. Role Overview The Lead Business Strategic Insights role partners closely with leaders across Commercial Strategy & Innovation (CSI) to develop data-driven solutions that accelerate business growth, enhance customer outcomes, and bring innovative products to market. This individual will leverage advanced analytics, artificial intelligence, machine learning, and business insights to solve complex challenges, uncover opportunities, and drive strategic decision-making across the organization. This role will participate throughout the full solution lifecycle, from ideation and proof of concept through production deployment and business adoption. Success in this position requires a combination of analytical expertise, business acumen, technical proficiency, and stakeholder influence. Key Responsibilities Accelerate AI-enabled decision-making by partnering with data governance, product, and technology teams to leverage governed data assets, semantic layers, and AI/LLM technologies that enable business users to access trusted insights more efficiently. Design and develop heuristics, optimization models, and advanced analytics solutions across customer, product, and operational domains to improve business outcomes. Utilize qualitative and quantitative data to identify opportunities, develop hypotheses, pilot proof-of-concept solutions, and scale successful models across the enterprise. Apply data science and analytical methodologies to identify market trends, process improvement opportunities, strategic synergies, and actionable business recommendations. Support digital data acquisition and integration strategies while building scalable data pipelines that complement existing enterprise data assets. Leverage CSI's data infrastructure to develop next-generation analytical models focused on customer value creation, margin expansion, and operational efficiencies. Drive experimentation and causal learning through pilots, A/B testing, and other measurement methodologies to quantify business impact and improve decision-making. Break down complex business challenges into scalable workstreams and collaborate across functional teams to drive solution adoption and implementation. Develop and deploy scalable Python-based APIs and data products that integrate with enterprise applications and business systems. Build and scale AI agents that enable business users to interact with data using natural language, uncover insights, identify opportunities, and make faster, more informed decisions. Present findings, recommendations, and business cases to senior leaders and cross-functional stakeholders. Minimum Requirements Bachelor's degree in Business, Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field, or equivalent experience. Typically requires 7+ years of relevant professional experience in analytics, data science, business intelligence, strategy, or a related discipline. Critical Skills 5+ years of experience in analytics, data science, business intelligence, or a related field. Proven experience leveraging analytics to drive measurable business value and strategic outcomes. Strong understanding of software engineering principles and API development used to commercialize analytical products and solutions. Advanced communication, presentation, and stakeholder management skills. Hands-on experience with Python, including libraries such as Pandas, Scikit-learn, NumPy, and related tools. Advanced SQL skills with experience querying and manipulating large, complex datasets. Strong understanding of machine learning techniques, including clustering, regression, anomaly detection, forecasting, classification, deep learning, and time series analysis. Experience working with cloud-based data platforms and modern analytics ecosystems. Experience building, deploying, or leveraging AI and generative AI solutions within business environments. Preferred Qualifications Experience working in healthcare, distribution, pharmaceutical, or supply chain environments. Experience with experimental design, causal inference, and business impact measurement. Familiarity with modern AI frameworks, large language models (LLMs), and agentic AI solutions. Experience building scalable data products and deploying machine learning models into production environments. Demonstrated success influencing business decisions through analytics and strategic insights. Additional Skills Passion for using data to solve complex business problems. Strong business acumen and strategic thinking capabilities. Ability to balance technical depth with business priorities. Self-starter with a continuous improvement mindset. Strong collaboration and relationship-building skills across functions and leadership levels. This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. 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 $136,300 - $227,100 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!
11/14/2026
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. Role Overview The Lead Business Strategic Insights role partners closely with leaders across Commercial Strategy & Innovation (CSI) to develop data-driven solutions that accelerate business growth, enhance customer outcomes, and bring innovative products to market. This individual will leverage advanced analytics, artificial intelligence, machine learning, and business insights to solve complex challenges, uncover opportunities, and drive strategic decision-making across the organization. This role will participate throughout the full solution lifecycle, from ideation and proof of concept through production deployment and business adoption. Success in this position requires a combination of analytical expertise, business acumen, technical proficiency, and stakeholder influence. Key Responsibilities Accelerate AI-enabled decision-making by partnering with data governance, product, and technology teams to leverage governed data assets, semantic layers, and AI/LLM technologies that enable business users to access trusted insights more efficiently. Design and develop heuristics, optimization models, and advanced analytics solutions across customer, product, and operational domains to improve business outcomes. Utilize qualitative and quantitative data to identify opportunities, develop hypotheses, pilot proof-of-concept solutions, and scale successful models across the enterprise. Apply data science and analytical methodologies to identify market trends, process improvement opportunities, strategic synergies, and actionable business recommendations. Support digital data acquisition and integration strategies while building scalable data pipelines that complement existing enterprise data assets. Leverage CSI's data infrastructure to develop next-generation analytical models focused on customer value creation, margin expansion, and operational efficiencies. Drive experimentation and causal learning through pilots, A/B testing, and other measurement methodologies to quantify business impact and improve decision-making. Break down complex business challenges into scalable workstreams and collaborate across functional teams to drive solution adoption and implementation. Develop and deploy scalable Python-based APIs and data products that integrate with enterprise applications and business systems. Build and scale AI agents that enable business users to interact with data using natural language, uncover insights, identify opportunities, and make faster, more informed decisions. Present findings, recommendations, and business cases to senior leaders and cross-functional stakeholders. Minimum Requirements Bachelor's degree in Business, Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field, or equivalent experience. Typically requires 7+ years of relevant professional experience in analytics, data science, business intelligence, strategy, or a related discipline. Critical Skills 5+ years of experience in analytics, data science, business intelligence, or a related field. Proven experience leveraging analytics to drive measurable business value and strategic outcomes. Strong understanding of software engineering principles and API development used to commercialize analytical products and solutions. Advanced communication, presentation, and stakeholder management skills. Hands-on experience with Python, including libraries such as Pandas, Scikit-learn, NumPy, and related tools. Advanced SQL skills with experience querying and manipulating large, complex datasets. Strong understanding of machine learning techniques, including clustering, regression, anomaly detection, forecasting, classification, deep learning, and time series analysis. Experience working with cloud-based data platforms and modern analytics ecosystems. Experience building, deploying, or leveraging AI and generative AI solutions within business environments. Preferred Qualifications Experience working in healthcare, distribution, pharmaceutical, or supply chain environments. Experience with experimental design, causal inference, and business impact measurement. Familiarity with modern AI frameworks, large language models (LLMs), and agentic AI solutions. Experience building scalable data products and deploying machine learning models into production environments. Demonstrated success influencing business decisions through analytics and strategic insights. Additional Skills Passion for using data to solve complex business problems. Strong business acumen and strategic thinking capabilities. Ability to balance technical depth with business priorities. Self-starter with a continuous improvement mindset. Strong collaboration and relationship-building skills across functions and leadership levels. This role is a hybrid position. The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities. 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 $136,300 - $227,100 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!
Pay Range: $60.00hr - $65.00hr Job Overview: As an Engineer, the candidate is responsible for building, designing, and deploying modern web applications. The candidate will leverage technical skills to architect scalable and robust solutions, tackle dependencies, and shape the team's technical strategy. Our client is looking for a Senior AI Engineer with Java Full Stack Experience to join a learner-centered team committed to delivering a next-generation transformative AI-powered learning infrastructure. In this role, the candidate will influence the future of learning experiences by developing integrated and scalable solutions from the ground up within a supportive and collaborative environment. Responsibilities: Collaborate closely with subject matter experts to understand challenges and translate them into effective solution designs, partnering with Product, UX, and other engineering teams. Drive AI efforts including Gemini integrations, ML model fine-tuning, evaluation, and performance optimization to create user-facing solutions that are both scalable and high-performant. Drive cross-functional collaboration to prototype web solutions, gather feedback, and iteratively refine requirements. Develop, test, and monitor robust, scalable, and reliable web solutions that meet business needs. Leverage cloud solutions and tools to create seamlessly integrated, reusable, and extensible systems. Write and review technical documents (product, technical design, developer documentation) and code in Angular, TypeScript, Java, Kotlin, Python, or SQL. Build the organization's agentic future by implementing Gemini integrations, assisting with ML model fine-tuning, and executing AI performance evaluations to help develop intelligent, user-facing learning solutions. Design, build, and deploy full-stack web solutions that are reliable, scalable, and high-performant, using advanced technologies to build AI-powered learning flows. Minimum qualifications: Bachelor's degree or equivalent practical experience. 10+ years of experience with Software Development in Java Fullstack (Java, Angular). 2+ years of experience in AI Technologies. Generative AI & LLMs: Demonstrated track record of deploying Gemini models in production using Vertex AI and the Agent Development Kit (ADK). RAG Architecture: Proven expertise in designing RAG systems. Backend & Cloud Infrastructure: Strong proficiency in Python (FastAPI), Cloud Run, and large-scale data retrieval strategies. Data Structures & Storage: Experience with relational database architecture and enterprise data schema management. Experience working with one or more of the following: web or mobile application development, Unix/Linux environments, distributed and parallel systems, machine learning, information retrieval, natural language processing, networking, developing software systems, or security. Strong verbal and written communication skills with stakeholder management capabilities. Preferred qualifications: Demonstrated experience with service architecture, domain-driven design, and the development of scalable, distributed services. Demonstrated experience in the end-to-end design, scaling, and performance tuning of AI-integrated web applications within dynamic environments. Demonstrated experience running Kanban boards and sprints while forecasting effort for complex engineering projects. Demonstrated experience with ADK, MCP, and integrating Gemini AI APIs into production web applications. Demonstrated experience with ML model fine-tuning, evaluation, and performance optimization for user-facing systems. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
11/14/2026
Full time
Pay Range: $60.00hr - $65.00hr Job Overview: As an Engineer, the candidate is responsible for building, designing, and deploying modern web applications. The candidate will leverage technical skills to architect scalable and robust solutions, tackle dependencies, and shape the team's technical strategy. Our client is looking for a Senior AI Engineer with Java Full Stack Experience to join a learner-centered team committed to delivering a next-generation transformative AI-powered learning infrastructure. In this role, the candidate will influence the future of learning experiences by developing integrated and scalable solutions from the ground up within a supportive and collaborative environment. Responsibilities: Collaborate closely with subject matter experts to understand challenges and translate them into effective solution designs, partnering with Product, UX, and other engineering teams. Drive AI efforts including Gemini integrations, ML model fine-tuning, evaluation, and performance optimization to create user-facing solutions that are both scalable and high-performant. Drive cross-functional collaboration to prototype web solutions, gather feedback, and iteratively refine requirements. Develop, test, and monitor robust, scalable, and reliable web solutions that meet business needs. Leverage cloud solutions and tools to create seamlessly integrated, reusable, and extensible systems. Write and review technical documents (product, technical design, developer documentation) and code in Angular, TypeScript, Java, Kotlin, Python, or SQL. Build the organization's agentic future by implementing Gemini integrations, assisting with ML model fine-tuning, and executing AI performance evaluations to help develop intelligent, user-facing learning solutions. Design, build, and deploy full-stack web solutions that are reliable, scalable, and high-performant, using advanced technologies to build AI-powered learning flows. Minimum qualifications: Bachelor's degree or equivalent practical experience. 10+ years of experience with Software Development in Java Fullstack (Java, Angular). 2+ years of experience in AI Technologies. Generative AI & LLMs: Demonstrated track record of deploying Gemini models in production using Vertex AI and the Agent Development Kit (ADK). RAG Architecture: Proven expertise in designing RAG systems. Backend & Cloud Infrastructure: Strong proficiency in Python (FastAPI), Cloud Run, and large-scale data retrieval strategies. Data Structures & Storage: Experience with relational database architecture and enterprise data schema management. Experience working with one or more of the following: web or mobile application development, Unix/Linux environments, distributed and parallel systems, machine learning, information retrieval, natural language processing, networking, developing software systems, or security. Strong verbal and written communication skills with stakeholder management capabilities. Preferred qualifications: Demonstrated experience with service architecture, domain-driven design, and the development of scalable, distributed services. Demonstrated experience in the end-to-end design, scaling, and performance tuning of AI-integrated web applications within dynamic environments. Demonstrated experience running Kanban boards and sprints while forecasting effort for complex engineering projects. Demonstrated experience with ADK, MCP, and integrating Gemini AI APIs into production web applications. Demonstrated experience with ML model fine-tuning, evaluation, and performance optimization for user-facing systems. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA) Disability Insurance (Short-Term and Long-Term) Life and AD&D Insurance Paid Sick Leave (where required by applicable state or local law) Supplemental Insurance Plans Identity Theft Protection Pet Insurance Employee Wellness Programs Employee Assistance Program (EAP) Career Growth and Professional Development Opportunities Disclaimer: Benefits eligibility, accrual rates, and usage limits may vary based on employment status, length of service, and work location. Paid Sick Leave is provided in strict accordance with applicable state and municipal mandates. Cynet Systems Inc. reserves the right to modify, amend, or terminate any benefit plans at any time in accordance with applicable laws. About Cynet Systems Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. is a leading technology staffing and workforce solutions company serving Fortune 500 companies, government agencies, and enterprise organizations across the United States and Canada. We deliver agile, scalable talent solutions across IT, engineering, life sciences, clinical, and professional staffing, powered by a high-performing recruitment engine operating across North America and Asia. As a nationally and locally certified Minority Business Enterprise (MBE), Cynet Systems is committed to helping organizations build high-performing teams while empowering professionals to grow rewarding careers. Our organization is certified to ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II standards, reflecting our commitment to quality, security, operational excellence, and customer success.
Job Description C&F is a technology services company providing innovative solutions in Data Management, Big Data, Advanced Analytics and Compliance. With a highly integrated team of 400+ experts, for over 20 years C&F has been delivering superior engineering and premium operations to Fortune 500 companies, primarily in the Life Science industry. About Our Manufacturing Business Unit Our company is organized into unique Business Units, each delivering innovative and differentiated business technology solutions across industries. The Manufacturing Business Unit specializes in enterprise-scale manufacturing solutions that drive site- and network-level outcomes aligned to strategic objectives and KPIs. Our applications, data products, and advanced platform technologies-including AI and IoT-enable Digital Manufacturing at Scale. We primarily serve enterprise clients across Human Pharma, Animal Health, and Consumer Goods industries. Our Manufacturing Business Unit operates through three integrated functions: • Strategy & Growth - Develops differentiated offerings and industry thought leadership. • Business Consulting - Defines client-customized solutions and ensures sustained value realization. • Engineering Delivery - Delivers solution architecture, development, deployment, and sustainment. The Business Consulting function is hiring a Manager, Manufacturing Solutions Business Consultant to serve as a Product Owner and consulting lead across manufacturing digital initiatives. Position Overview The Consultant supports delivery of Digital Manufacturing initiatives by acting as a Business Analyst and/or Junior Product Owner within client engagements. This role partners closely with Managers and Senior Managers to define requirements, structure documentation, develop client-ready materials, and support Agile delivery execution. The Consultant plays a key role in translating manufacturing business needs into functional artifacts that enable engineering teams to deliver value. This is a hands-on, consulting and analytical role suited for individuals with early experience in Manufacturing OT, Manufacturing IT or technology. The role also requires a working understanding of artificial intelligence (AI), including generative AI and agentic technologies, and an interest in applying these capabilities to practical manufacturing and business challenges. Key Responsibilities Consulting & Problem Solving Support consulting engagements by analyzing manufacturing business needs, contributing to client discussions, and helping develop practical recommendations and solutions. Business Analysis & Requirements Development • Support facilitation of client workshops to gather functional and non-functional requirements. • Document business processes, current-state pain points, and future-state solution designs. • Develop structured requirements documentation, user stories, and acceptance criteria. • Assist in translating manufacturing KPIs (OEE, quality, throughput, asset performance) into measurable solution objectives. • Maintain traceability between business requirements and delivered functionality. Product & Backlog Support • Support backlog development and refinement under guidance of a Manager or Senior Manager. • Draft epics, features, and user stories aligned to defined roadmap priorities. • Participate in sprint planning, demos, and retrospectives. • Track action items, risks, and dependencies across delivery workstreams. • Assist in maintaining roadmap documentation and milestone trackers. Documentation & Presentation Development Develop high-quality client-ready materials including: Roadmap summaries Workshop outputs Business case inputs Solution overviews Executive presentation drafts: -Structure content using clear, logical storytelling and data-supported insights. -Support development of proposal materials and Statements of Work. -Ensure documentation is clear, concise, and professionally formatted. Agile & Delivery Support • Operate within Agile delivery models (Scrum, SAFe, or hybrid environments). • Support backlog grooming and sprint documentation. • Assist with tracking sprint progress and updating delivery artifacts. • Promote disciplined documentation and communication standards. Manufacturing Domain & Technical Acumen • Build working knowledge of manufacturing business processes (production execution, quality, maintenance, traceability). • Develop familiarity with manufacturing technology ecosystems • Support analysis of integration points across MES, ERP, IoT, and data platforms. AI & Agentic Solution Support • Support identification and documentation of AI-enabled use cases across manufacturing processes, knowledge workflows, decision support, and task automation. • Translate AI use cases into business requirements, process flows, user stories, acceptance criteria, test scenarios, and measurable success criteria. • Build familiarity with large language models, AI agents, retrieval-augmented generation, machine learning, and enterprise AI governance concepts. Required Qualifications • 3+ years of consulting experience in manufacturing, technology, or digital delivery environments. • Proven consulting experience supporting client discussions and helping develop practical recommendations and solutions. • Experience supporting requirements gathering and documentation. • Exposure to Agile delivery methodologies. • Strong written and verbal communication skills. • Analytical mindset with structured problem-solving capabilities. • Proficiency in presentation development tools (e.g., PowerPoint, Excel). Preferred Qualifications • Bachelor's degree • Experience in technology delivery or implementation • Experience with project management practices and project management software • Experience working with cross functional teams such as UI/UX designers, software/data engineers and end users What we offer: Competitive remuneration and various benefits: 401(k) Retirement Plan (Immediate eligibility with 100% employer match up to 4%.) Medical Insurance Maternity and Paternity Leave Long-Term Disability Bereavement leave Generous Sick Leave Internet and Phone stipend Development stipend Wellness stipend Generous Paid Time Off: 20 days in the first year, increasing to 25 days We work fully remotely but expect openness to occasional travel Company culture is rooted in respect and cooperation. You'll be working with great people, who are open to new challenges and directions. If you are tired of the proverbial corporate treadmill, come to us to rest mentally. If you've had luck with employers, we'll do our best not to buck the trend. Additional Info: Range: $100,000 - $115,000 + Bonus Location: Remote (US East Coast) Travel: 10%
11/14/2026
Full time
Job Description C&F is a technology services company providing innovative solutions in Data Management, Big Data, Advanced Analytics and Compliance. With a highly integrated team of 400+ experts, for over 20 years C&F has been delivering superior engineering and premium operations to Fortune 500 companies, primarily in the Life Science industry. About Our Manufacturing Business Unit Our company is organized into unique Business Units, each delivering innovative and differentiated business technology solutions across industries. The Manufacturing Business Unit specializes in enterprise-scale manufacturing solutions that drive site- and network-level outcomes aligned to strategic objectives and KPIs. Our applications, data products, and advanced platform technologies-including AI and IoT-enable Digital Manufacturing at Scale. We primarily serve enterprise clients across Human Pharma, Animal Health, and Consumer Goods industries. Our Manufacturing Business Unit operates through three integrated functions: • Strategy & Growth - Develops differentiated offerings and industry thought leadership. • Business Consulting - Defines client-customized solutions and ensures sustained value realization. • Engineering Delivery - Delivers solution architecture, development, deployment, and sustainment. The Business Consulting function is hiring a Manager, Manufacturing Solutions Business Consultant to serve as a Product Owner and consulting lead across manufacturing digital initiatives. Position Overview The Consultant supports delivery of Digital Manufacturing initiatives by acting as a Business Analyst and/or Junior Product Owner within client engagements. This role partners closely with Managers and Senior Managers to define requirements, structure documentation, develop client-ready materials, and support Agile delivery execution. The Consultant plays a key role in translating manufacturing business needs into functional artifacts that enable engineering teams to deliver value. This is a hands-on, consulting and analytical role suited for individuals with early experience in Manufacturing OT, Manufacturing IT or technology. The role also requires a working understanding of artificial intelligence (AI), including generative AI and agentic technologies, and an interest in applying these capabilities to practical manufacturing and business challenges. Key Responsibilities Consulting & Problem Solving Support consulting engagements by analyzing manufacturing business needs, contributing to client discussions, and helping develop practical recommendations and solutions. Business Analysis & Requirements Development • Support facilitation of client workshops to gather functional and non-functional requirements. • Document business processes, current-state pain points, and future-state solution designs. • Develop structured requirements documentation, user stories, and acceptance criteria. • Assist in translating manufacturing KPIs (OEE, quality, throughput, asset performance) into measurable solution objectives. • Maintain traceability between business requirements and delivered functionality. Product & Backlog Support • Support backlog development and refinement under guidance of a Manager or Senior Manager. • Draft epics, features, and user stories aligned to defined roadmap priorities. • Participate in sprint planning, demos, and retrospectives. • Track action items, risks, and dependencies across delivery workstreams. • Assist in maintaining roadmap documentation and milestone trackers. Documentation & Presentation Development Develop high-quality client-ready materials including: Roadmap summaries Workshop outputs Business case inputs Solution overviews Executive presentation drafts: -Structure content using clear, logical storytelling and data-supported insights. -Support development of proposal materials and Statements of Work. -Ensure documentation is clear, concise, and professionally formatted. Agile & Delivery Support • Operate within Agile delivery models (Scrum, SAFe, or hybrid environments). • Support backlog grooming and sprint documentation. • Assist with tracking sprint progress and updating delivery artifacts. • Promote disciplined documentation and communication standards. Manufacturing Domain & Technical Acumen • Build working knowledge of manufacturing business processes (production execution, quality, maintenance, traceability). • Develop familiarity with manufacturing technology ecosystems • Support analysis of integration points across MES, ERP, IoT, and data platforms. AI & Agentic Solution Support • Support identification and documentation of AI-enabled use cases across manufacturing processes, knowledge workflows, decision support, and task automation. • Translate AI use cases into business requirements, process flows, user stories, acceptance criteria, test scenarios, and measurable success criteria. • Build familiarity with large language models, AI agents, retrieval-augmented generation, machine learning, and enterprise AI governance concepts. Required Qualifications • 3+ years of consulting experience in manufacturing, technology, or digital delivery environments. • Proven consulting experience supporting client discussions and helping develop practical recommendations and solutions. • Experience supporting requirements gathering and documentation. • Exposure to Agile delivery methodologies. • Strong written and verbal communication skills. • Analytical mindset with structured problem-solving capabilities. • Proficiency in presentation development tools (e.g., PowerPoint, Excel). Preferred Qualifications • Bachelor's degree • Experience in technology delivery or implementation • Experience with project management practices and project management software • Experience working with cross functional teams such as UI/UX designers, software/data engineers and end users What we offer: Competitive remuneration and various benefits: 401(k) Retirement Plan (Immediate eligibility with 100% employer match up to 4%.) Medical Insurance Maternity and Paternity Leave Long-Term Disability Bereavement leave Generous Sick Leave Internet and Phone stipend Development stipend Wellness stipend Generous Paid Time Off: 20 days in the first year, increasing to 25 days We work fully remotely but expect openness to occasional travel Company culture is rooted in respect and cooperation. You'll be working with great people, who are open to new challenges and directions. If you are tired of the proverbial corporate treadmill, come to us to rest mentally. If you've had luck with employers, we'll do our best not to buck the trend. Additional Info: Range: $100,000 - $115,000 + Bonus Location: Remote (US East Coast) Travel: 10%
Job Description Intellibus Consulting is a boutique engineering and AI transformation firm that builds mission-critical platforms for global financial institutions. We operate at the intersection of engineering excellence, business outcomes, and executive-level delivery. At Intellibus, our leaders are hands-on builders who understand technology deeply, engage confidently with senior executives, and take ownership of client success. We believe successful technology transformation requires leaders who can connect business strategy, architecture, engineering, and execution Job Description We are looking for exceptional Forward Deployed Engineers with deep hands-on software engineering expertise, particularly in Java, backend engineering, full-stack development, microservices, and distributed systems. This is a highly technical, client-facing engineering role that requires someone who can move seamlessly between architecture, software development, solution delivery, and executive-level client engagement. You will work directly with client engineering teams, technology leaders, and business stakeholders to understand complex challenges, design technical solutions, and lead the development and implementation of enterprise-grade platforms. Beyond engineering delivery, you will play an important role in expanding strategic client relationships by identifying technology opportunities, recommending solutions, demonstrating technical capabilities, and helping grow existing accounts. We are specifically looking for engineers who have worked in technology consulting or professional services environments and are comfortable taking ownership of both technical delivery and client relationships. Key Responsibilities Hands-on Software Engineering & Architecture Design, develop, and deliver scalable enterprise applications using Java and modern software engineering technologies. Demonstrate deep hands-on expertise in Java, Spring Boot, Spring Framework, REST APIs, and backend application development. Build complex microservices-based architectures, distributed systems, and event-driven applications. Develop full-stack solutions with strong backend capabilities and practical frontend development experience. Work across the entire software development lifecycle, from architecture and design through coding, testing, deployment, and production support. Lead technical implementation while remaining actively involved in writing and reviewing code. Develop reusable components, APIs, integrations, and enterprise application frameworks. Troubleshoot performance bottlenecks, scalability challenges, concurrency issues, and complex production defects. Backend, Frontend & Full-Stack Development Build backend services using Java, Spring Boot, Hibernate, JPA, and related technologies. Design and implement RESTful APIs, microservices, and enterprise integrations. Develop frontend applications using React, JavaScript, TypeScript, HTML, and CSS. Integrate frontend applications with backend services and enterprise platforms. Work with relational and NoSQL databases, including PostgreSQL, Oracle, MongoDB, or similar technologies. Implement authentication, authorization, security, and API integration patterns. Ensure application performance, maintainability, reliability, and scalability. Microservices & Cloud-Native Engineering Design and implement microservices architectures and distributed application platforms. Work with messaging and event-streaming technologies such as Apache Kafka. Build asynchronous processing, event-driven integrations, and resilient distributed services. Apply design patterns for service discovery, fault tolerance, circuit breakers, and distributed transactions. Deploy and operate applications on AWS, Azure, or GCP. Work with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation. Apply observability practices using logging, monitoring, tracing, and performance management tools. Understand cloud-native architecture, scalability, availability, and system reliability. AI & Agentic Engineering Explore and implement AI-powered enterprise applications and intelligent workflows. Integrate LLMs and AI capabilities into existing enterprise applications and platforms. Develop AI agents, tool-calling workflows, and agent orchestration capabilities. Work with retrieval-augmented generation (RAG), vector databases, and enterprise data integrations. Identify opportunities to apply AI and automation to solve client business and technology challenges. Build practical prototypes and take successful AI solutions through production implementation. Client Consulting & Strategic Account Growth Work directly with client CTOs, CIOs, engineering leaders, architects, and business stakeholders. Understand client technology environments, business priorities, and strategic challenges. Translate business problems into technical solutions and actionable engineering roadmaps. Lead technical discovery sessions, architecture discussions, solution demonstrations, and client workshops. Identify opportunities for platform modernization, application development, cloud transformation, and AI adoption. Help expand existing client engagements by identifying new projects, engineering opportunities, and areas where Intellibus can add value. Build trusted relationships with client stakeholders and contribute to long-term account growth. Prepare technical proposals, solution presentations, architecture diagrams, and executive-level materials. Collaborate with leadership and account teams to shape new opportunities and support business development. Required Technical Expertise Java & Backend Engineering Extensive hands-on experience with Java and Spring Boot. Strong understanding of OOP, multithreading, concurrency, collections, JVM fundamentals, and performance optimization. Experience with REST APIs, Hibernate, JPA, and enterprise application development. Strong knowledge of backend architecture and enterprise integration patterns. Full-Stack Development Experience building frontend applications using React, JavaScript, and TypeScript. Ability to independently work across backend and frontend components. Strong understanding of API integration and application architecture. Microservices & Distributed Systems Deep experience designing and implementing microservices architectures. Strong knowledge of Kafka, event-driven systems, messaging, and distributed computing. Understanding of scalability, resiliency, fault tolerance, and high-availability architecture. Cloud & DevOps Experience with AWS, Azure, or GCP. Hands-on experience with Docker, Kubernetes, CI/CD, and cloud-native deployments. Familiarity with Terraform or other infrastructure-as-code tools is preferred. AI & Modern Engineering Exposure to LLM integrations, generative AI, AI agents, and agentic workflows. Experience integrating AI capabilities into enterprise software is highly desirable. Required Consulting & Client Engagement Experience Previous experience working for a technology consulting firm, systems integrator, or professional services organization is mandatory. Demonstrated experience delivering technology solutions for external enterprise clients. Ability to manage multiple technical stakeholders and work across different client environments. Strong executive communication and presentation skills. Ability to identify additional technology opportunities and contribute to account expansion. Comfortable operating in fast-paced consulting environments where priorities and client requirements can evolve. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience. Significant professional software engineering experience, ideally 8+ years. Extensive hands-on Java and backend engineering experience. Proven experience building enterprise-grade microservices and distributed systems. Full-stack development experience with modern frontend frameworks. Previous consulting or professional services experience is mandatory. Experience working in financial services, banking, fintech, or other regulated industries is strongly preferred. What Success Looks Like You can independently design, code, and deliver complex enterprise applications. You bring deep technical expertise in Java, backend engineering, full-stack development, and microservices. You can engage with client engineering teams and senior executives with equal confidence. You identify opportunities to solve broader client challenges beyond the immediate assignment. You help strengthen client relationships and contribute to expanding strategic accounts. You take ownership of solutions from initial discovery through architecture, implementation, and production deployment. Who Should Apply? We are looking for engineers who are not limited to writing code against predefined requirements. . click apply for full job details
11/14/2026
Full time
Job Description Intellibus Consulting is a boutique engineering and AI transformation firm that builds mission-critical platforms for global financial institutions. We operate at the intersection of engineering excellence, business outcomes, and executive-level delivery. At Intellibus, our leaders are hands-on builders who understand technology deeply, engage confidently with senior executives, and take ownership of client success. We believe successful technology transformation requires leaders who can connect business strategy, architecture, engineering, and execution Job Description We are looking for exceptional Forward Deployed Engineers with deep hands-on software engineering expertise, particularly in Java, backend engineering, full-stack development, microservices, and distributed systems. This is a highly technical, client-facing engineering role that requires someone who can move seamlessly between architecture, software development, solution delivery, and executive-level client engagement. You will work directly with client engineering teams, technology leaders, and business stakeholders to understand complex challenges, design technical solutions, and lead the development and implementation of enterprise-grade platforms. Beyond engineering delivery, you will play an important role in expanding strategic client relationships by identifying technology opportunities, recommending solutions, demonstrating technical capabilities, and helping grow existing accounts. We are specifically looking for engineers who have worked in technology consulting or professional services environments and are comfortable taking ownership of both technical delivery and client relationships. Key Responsibilities Hands-on Software Engineering & Architecture Design, develop, and deliver scalable enterprise applications using Java and modern software engineering technologies. Demonstrate deep hands-on expertise in Java, Spring Boot, Spring Framework, REST APIs, and backend application development. Build complex microservices-based architectures, distributed systems, and event-driven applications. Develop full-stack solutions with strong backend capabilities and practical frontend development experience. Work across the entire software development lifecycle, from architecture and design through coding, testing, deployment, and production support. Lead technical implementation while remaining actively involved in writing and reviewing code. Develop reusable components, APIs, integrations, and enterprise application frameworks. Troubleshoot performance bottlenecks, scalability challenges, concurrency issues, and complex production defects. Backend, Frontend & Full-Stack Development Build backend services using Java, Spring Boot, Hibernate, JPA, and related technologies. Design and implement RESTful APIs, microservices, and enterprise integrations. Develop frontend applications using React, JavaScript, TypeScript, HTML, and CSS. Integrate frontend applications with backend services and enterprise platforms. Work with relational and NoSQL databases, including PostgreSQL, Oracle, MongoDB, or similar technologies. Implement authentication, authorization, security, and API integration patterns. Ensure application performance, maintainability, reliability, and scalability. Microservices & Cloud-Native Engineering Design and implement microservices architectures and distributed application platforms. Work with messaging and event-streaming technologies such as Apache Kafka. Build asynchronous processing, event-driven integrations, and resilient distributed services. Apply design patterns for service discovery, fault tolerance, circuit breakers, and distributed transactions. Deploy and operate applications on AWS, Azure, or GCP. Work with Docker, Kubernetes, CI/CD pipelines, and infrastructure automation. Apply observability practices using logging, monitoring, tracing, and performance management tools. Understand cloud-native architecture, scalability, availability, and system reliability. AI & Agentic Engineering Explore and implement AI-powered enterprise applications and intelligent workflows. Integrate LLMs and AI capabilities into existing enterprise applications and platforms. Develop AI agents, tool-calling workflows, and agent orchestration capabilities. Work with retrieval-augmented generation (RAG), vector databases, and enterprise data integrations. Identify opportunities to apply AI and automation to solve client business and technology challenges. Build practical prototypes and take successful AI solutions through production implementation. Client Consulting & Strategic Account Growth Work directly with client CTOs, CIOs, engineering leaders, architects, and business stakeholders. Understand client technology environments, business priorities, and strategic challenges. Translate business problems into technical solutions and actionable engineering roadmaps. Lead technical discovery sessions, architecture discussions, solution demonstrations, and client workshops. Identify opportunities for platform modernization, application development, cloud transformation, and AI adoption. Help expand existing client engagements by identifying new projects, engineering opportunities, and areas where Intellibus can add value. Build trusted relationships with client stakeholders and contribute to long-term account growth. Prepare technical proposals, solution presentations, architecture diagrams, and executive-level materials. Collaborate with leadership and account teams to shape new opportunities and support business development. Required Technical Expertise Java & Backend Engineering Extensive hands-on experience with Java and Spring Boot. Strong understanding of OOP, multithreading, concurrency, collections, JVM fundamentals, and performance optimization. Experience with REST APIs, Hibernate, JPA, and enterprise application development. Strong knowledge of backend architecture and enterprise integration patterns. Full-Stack Development Experience building frontend applications using React, JavaScript, and TypeScript. Ability to independently work across backend and frontend components. Strong understanding of API integration and application architecture. Microservices & Distributed Systems Deep experience designing and implementing microservices architectures. Strong knowledge of Kafka, event-driven systems, messaging, and distributed computing. Understanding of scalability, resiliency, fault tolerance, and high-availability architecture. Cloud & DevOps Experience with AWS, Azure, or GCP. Hands-on experience with Docker, Kubernetes, CI/CD, and cloud-native deployments. Familiarity with Terraform or other infrastructure-as-code tools is preferred. AI & Modern Engineering Exposure to LLM integrations, generative AI, AI agents, and agentic workflows. Experience integrating AI capabilities into enterprise software is highly desirable. Required Consulting & Client Engagement Experience Previous experience working for a technology consulting firm, systems integrator, or professional services organization is mandatory. Demonstrated experience delivering technology solutions for external enterprise clients. Ability to manage multiple technical stakeholders and work across different client environments. Strong executive communication and presentation skills. Ability to identify additional technology opportunities and contribute to account expansion. Comfortable operating in fast-paced consulting environments where priorities and client requirements can evolve. Qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience. Significant professional software engineering experience, ideally 8+ years. Extensive hands-on Java and backend engineering experience. Proven experience building enterprise-grade microservices and distributed systems. Full-stack development experience with modern frontend frameworks. Previous consulting or professional services experience is mandatory. Experience working in financial services, banking, fintech, or other regulated industries is strongly preferred. What Success Looks Like You can independently design, code, and deliver complex enterprise applications. You bring deep technical expertise in Java, backend engineering, full-stack development, and microservices. You can engage with client engineering teams and senior executives with equal confidence. You identify opportunities to solve broader client challenges beyond the immediate assignment. You help strengthen client relationships and contribute to expanding strategic accounts. You take ownership of solutions from initial discovery through architecture, implementation, and production deployment. Who Should Apply? We are looking for engineers who are not limited to writing code against predefined requirements. . click apply for full job details
Job Description Job Description Genesis10 is currently seeking a Senior AI Engineer (Generative AI & Agentic Systems) for a contract position with a Global Financial Institution located in Pennington, NJ. This is a 12+ month contract opportunity. We are seeking an Advanced Python Engineer with specialized expertise in Generative AI orchestration, multi-agent workflows, and Retrieval-Augmented Generation (RAG) systems. In this role, you will design, build, and scale production-grade LLM applications, leveraging modern agentic frameworks to power intelligent enterprise solutions. Key Responsibilities: Architect and scale advanced Retrieval-Augmented Generation (RAG) pipelines, including custom chunking, hybrid search, embedding optimization, and reranking mechanisms Build complex, stateful multi-agent systems and autonomous workflows using frameworks such as LangGraph and Deepagents Orchestrate and monitor using LangChain for robust LLM integration and LangSmith for tracing, evaluation, debugging, and performance monitoring of production LLM pipelines Write clean, modular, highly efficient, and maintainable Python code adhering to modern standards (asynchronous programming, strict typing, and robust error handling) Connect LLM agents and workflows with external data sources, enterprise APIs, vector databases, and developer tooling Optimize token usage, latency, and operational costs across LLM-driven applications without compromising response quality or accuracy Requirements: Advanced, production-level proficiency in Python (asyncio, design patterns, profiling, and testing) Demonstrated hands-on production experience with one or more of the following: LangChain, LangGraph, LangSmith, Deepagents Deep working knowledge of RAG pipelines, prompt engineering strategies, and integration with vector databases (e.g., Pinecone, Weaviate, Milvus, Qdrant, or pgvector) Familiarity with major LLM providers (OpenAI, Anthropic, open-source models via Hugging Face/Ollama) and function-calling / tool-use architectures Experience with Git, CI/CD pipelines, containerization (Docker), and cloud environments (AWS, GCP, or Azure) Pay range: $55.06 - $63.06 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
11/13/2026
Full time
Job Description Job Description Genesis10 is currently seeking a Senior AI Engineer (Generative AI & Agentic Systems) for a contract position with a Global Financial Institution located in Pennington, NJ. This is a 12+ month contract opportunity. We are seeking an Advanced Python Engineer with specialized expertise in Generative AI orchestration, multi-agent workflows, and Retrieval-Augmented Generation (RAG) systems. In this role, you will design, build, and scale production-grade LLM applications, leveraging modern agentic frameworks to power intelligent enterprise solutions. Key Responsibilities: Architect and scale advanced Retrieval-Augmented Generation (RAG) pipelines, including custom chunking, hybrid search, embedding optimization, and reranking mechanisms Build complex, stateful multi-agent systems and autonomous workflows using frameworks such as LangGraph and Deepagents Orchestrate and monitor using LangChain for robust LLM integration and LangSmith for tracing, evaluation, debugging, and performance monitoring of production LLM pipelines Write clean, modular, highly efficient, and maintainable Python code adhering to modern standards (asynchronous programming, strict typing, and robust error handling) Connect LLM agents and workflows with external data sources, enterprise APIs, vector databases, and developer tooling Optimize token usage, latency, and operational costs across LLM-driven applications without compromising response quality or accuracy Requirements: Advanced, production-level proficiency in Python (asyncio, design patterns, profiling, and testing) Demonstrated hands-on production experience with one or more of the following: LangChain, LangGraph, LangSmith, Deepagents Deep working knowledge of RAG pipelines, prompt engineering strategies, and integration with vector databases (e.g., Pinecone, Weaviate, Milvus, Qdrant, or pgvector) Familiarity with major LLM providers (OpenAI, Anthropic, open-source models via Hugging Face/Ollama) and function-calling / tool-use architectures Experience with Git, CI/CD pipelines, containerization (Docker), and cloud environments (AWS, GCP, or Azure) Pay range: $55.06 - $63.06 per hour Only candidates available and ready to work directly as Genesis10 employees will be considered for this position. If you have the described qualifications and are interested in this exciting opportunity, please apply! Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts for six consecutive years, Genesis10 puts thousands of consultants and employees to work across the United States every year in contract, contract-for-hire, and permanent placement roles. With more than 300 active clients, Genesis10 provides access to many of the Fortune 100 firms and a variety of mid-market organizations across the full spectrum of industry verticals. For contract roles, Genesis10 offers the benefits listed below. If this is a perm-placement opportunity, our recruiter can talk you through the unique benefits offered for that particular client. Benefits of Working with Genesis10: Access to hundreds of clients, most who have been working with Genesis10 for 5-20+ years. The opportunity to have a career-home in Genesis10; many of our consultants have been working exclusively with Genesis10 for years. Access to an experienced, caring recruiting team (more than 7 years of experience, on average.) Behavioral Health Platform Medical, Dental, Vision Health Savings Account Voluntary Hospital Indemnity (Critical Illness & Accident) Voluntary Term Life Insurance 401K Sick Pay (for applicable states/municipalities) Commuter Benefits (Dallas, NYC, SF, and Illinois) For multiple years running, Genesis10 has been recognized as a Top Staffing Firm in the U.S., as a Best Company for Work-Life Balance, as a Best Company for Career Growth, for Diversity, and for Leadership, amongst others. To learn more and to view all our available career opportunities, please visit us at our website. Genesis10 is an Equal Opportunity Employer. Candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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 The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development 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 . click apply for full job details
11/11/2026
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 The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development 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 . click apply for full job details
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 The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development 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 . click apply for full job details
11/11/2026
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 The Principal Data Scientist is the senior technical and scientific leader for AbbVie's omnichannel engagement analytics, a data and analytics-driven engagement optimization program spanning channel mix, content, field representative call planning, and orchestration. Operating within the APEX Enterprise Advanced Analytics and Innovation team, this role sets the multi-year science vision for personalized commercial engagement and is accountable for the technical strategy, methodology, and scientific rigor of the AI/ML and statistical solutions that power it. Reporting to the Associate Director, Data Science, the Principal is a thought partner to commercial and analytics leadership: shaping which problems are worth solving, forming and defending a point of view on how AI creates measurable business value, and partnering with product owners to turn that vision into scalable solutions. The role combines deep, hands-on expertise in applied machine learning, generative AI, causal inference, and experimentation with the consultative skill to align a complex stakeholder ecosystem around the right answer. Key Responsibilities Define the Data Science vision: Own the multi-year Data Science vision and technical roadmap for omnichannel engagement analytics, anticipating where both the business and the field of AI are heading. Shape how AI creates business value: identify, size, and prioritize opportunities where AI can drive measurable commercial impact, build the business case, and influence senior leadership decisions on where to invest. Lead hands-on with Gen-AI: Personally use AI-assisted development and agentic tools to prototype, test hypotheses, and demonstrate value quickly; build LLM-backed systems using advanced RAG and context engineering, paired with rigorous scientific evaluation frameworks to scale highly reliable omnichannel recommendations. Lead the design of predictive and causal models: Develop next-best-action, recommendation, and sequential decision models that inform customer engagement and resource allocation using complex, multi-source data. Own measurement science: set the standard for measuring effectiveness, incrementality, and business impact using experimental and quasi-experimental methods, so that AI investments are evaluated rigorously. Partner with product owners to shape problems, not just fulfill requirements: co-define business outcomes, scope, and success metrics, and translate them into scalable technical solutions. Navigate a complex stakeholder ecosystem: build alignment across brand and marketing leaders, field sales and operations, Medical, Legal and Regulatory (MLR), Compliance, BTS, Digital Lab, and external vendors; reframe requests into well-posed problems and resolve competing priorities. Communicate with executive impact: translate complex methods and findings into clear recommendations and compelling narratives for executive and non-technical audiences. Productionize at scale: Partner with BTS, Digital Lab, engineering, and platform teams to deploy, monitor, and manage the lifecycle of AI/ML solutions. Raise the bar for scientific rigor: establish best practices in model development, code quality, reproducibility, peer review, and responsible AI across the data science community. Be a thought leader: stay at the forefront of research and practice in machine learning, generative AI, and causal inference; bring new ideas into the team; provoke rigorous analytical debate; and represent AbbVie's point of view internally and in the broader analytics community. Supervisory / Management Responsibilities This role does not carry formal direct report responsibilities but is expected to act as a technical leader and mentor across the broader data science community, raising the bar on scientific rigor and hands-on AI practice. The Principal Data Scientist may lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation. Key Competencies Scientific Engineering Depth: Deep expertise in machine learning, causal inference, and generative AI, combined with strong engineering discipline in reproducibility, deployment, and enterprise integration. AI Fluency and Bias to Action: Uses AI hands-on in daily work to prototype, analyze, and build; critically evaluates AI output; and turns ideas into working solutions quickly. Business Judgment and Problem-Framing: Translates ambiguous business challenges into well-scoped problems, connects technical choices to commercial value, and sets long-term technical direction while staying close to delivery. Stakeholder Navigation and Executive Influence: Reads organizational dynamics to build alignment across commercial, regulatory, and technology partners, earning trust as a thought partner to win support from senior leaders. Thought Leadership: Challenges conventional thinking and sparks meaningful analytical debate with peers and executives. Qualifications Education Bachelor's Degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative discipline required; Master's or PhD in a quantitative field strongly preferred. Required Experience 8+ years of experience in data science, machine learning, or applied science (or 6+ years with a PhD), with a track record of delivering production-quality models that drove measurable business impact. Demonstrated experience setting technical direction for a portfolio of AI/ML solutions and influencing decisions of senior business leaders. Experience building personalization, recommendation, decision-optimization, or marketing-science solutions, in any industry. Deep hands-on expertise in causal inference and experimentation, including A/B testing and quasi-experimental methods, to measure business impact. Demonstrated hands-on experience using generative AI and AI-assisted development tools (e.g., LLM APIs, AI coding assistants, agent frameworks) to prototype and deliver solutions, with concrete examples that can be walked through during the interview process. Expert proficiency in Python and SQL, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow) and distributed data processing. Experience productionizing AI/ML solutions in cloud environments, including deployment, monitoring, and lifecycle management. Track record of leading initiatives across complex, cross-functional stakeholder environments and presenting to executive audiences. Preferred Experience Commercial analytics experience in pharmaceutical, biotech, healthcare, or life sciences, including familiarity with data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement data. Experience in omnichannel analytics, such as journey analysis, touchpoint measurement, closed-loop measurement, or next-best-action for HCP or patient engagement. Experience with advanced ML and optimization methods, including reinforcement learning, multi-armed bandits, transformers, and other approaches for sequential or recommendation use cases. Experience building LLM-based and agentic AI systems, including orchestration frameworks, evaluation, and integration through APIs and pipelines. Experience with cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow. External visibility through conference talks, publications, patents, open-source contributions, or recognized industry thought leadership. Experience working in agile product development 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 . click apply for full job details
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.
09/28/2026
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.