Job Description Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location Atlanta GA, Chicago IL, New York NY, San Francisco CA Your Role We are seeking an Anthropic Identity & Integration Lead to design, implement, and support secure enterprise deployments of Anthropic solutions. This role focuses on platform deployment, identity management, security integration, provisioning, administration, and enterprise connectivity. The successful candidate will work closely with customer IT, IAM, security, networking, and infrastructure teams to move implementations through security review, go-live readiness, provisioning, and initial production activation. • Lead technical kickoff and deployment workshops with customer IT, IAM, security, and infrastructure teams. • Assess customer environments, select the deployment path, and define the implementation plan. • Design and configure enterprise single sign-on using appropriate identity federation standards and providers. • Configure SCIM provisioning and support user lifecycle management. • Implement administrative policies, role-based access controls, and security configurations. • Configure Model Context Protocol (MCP) connectors and enterprise integrations where applicable. • Provision seats, users, groups, environments, and supported access surfaces. • Coordinate security reviews, compliance activities, testing, and go-live gates. • Collaborate with IAM, networking, cloud, application, and security teams to resolve deployment issues. • Develop implementation documentation, operating procedures, and technical runbooks. • Support initial cohort activation and transition the deployed service to ongoing operations. • Identify opportunities to extend the platform through Claude Code, Cowork, APIs, MCP, and custom AI solutions. Required Qualifications • Agentic AI development experience • Vibe coding experience with Claude Code • Complex task automation with Claude Cowork Required Skills and Experience • Master's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience. • Experience implementing enterprise SaaS platforms, cloud services, or identity-integrated applications. • Strong understanding of Identity and Access Management (IAM). • Experience configuring SSO using SAML, OAuth 2.0, or OpenID Connect. • Experience with SCIM provisioning and user lifecycle management. • Experience with enterprise security controls, access policies, and security review processes. • Understanding of APIs, network connectivity, and enterprise integration patterns. • Familiarity with at least one major cloud platform such as AWS, Microsoft Azure, or Google Cloud. • Strong troubleshooting, documentation, and technical diagnostic skills. • Experience working directly with enterprise IT and security organizations. Preferred Qualifications • Experience implementing Anthropic services or comparable enterprise AI platforms. • Experience with Model Context Protocol (MCP) servers, clients, or connectors. • Familiarity with Claude Code, Cowork, Anthropic APIs, and enterprise AI administration. • Experience with security governance, compliance, and risk-management processes. • Knowledge of enterprise architecture, API security, and integration patterns. • Consulting or customer-facing delivery experience. • Software engineering experience with Python, TypeScript, REST APIs, or cloud-native services. Key Competencies • Identity and access management • Enterprise integration • Secure platform deployment • Technical consulting • Cloud and SaaS administration • Governance and compliance • Problem solving and troubleshooting"
11/14/2026
Full time
Job Description Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Location Atlanta GA, Chicago IL, New York NY, San Francisco CA Your Role We are seeking an Anthropic Identity & Integration Lead to design, implement, and support secure enterprise deployments of Anthropic solutions. This role focuses on platform deployment, identity management, security integration, provisioning, administration, and enterprise connectivity. The successful candidate will work closely with customer IT, IAM, security, networking, and infrastructure teams to move implementations through security review, go-live readiness, provisioning, and initial production activation. • Lead technical kickoff and deployment workshops with customer IT, IAM, security, and infrastructure teams. • Assess customer environments, select the deployment path, and define the implementation plan. • Design and configure enterprise single sign-on using appropriate identity federation standards and providers. • Configure SCIM provisioning and support user lifecycle management. • Implement administrative policies, role-based access controls, and security configurations. • Configure Model Context Protocol (MCP) connectors and enterprise integrations where applicable. • Provision seats, users, groups, environments, and supported access surfaces. • Coordinate security reviews, compliance activities, testing, and go-live gates. • Collaborate with IAM, networking, cloud, application, and security teams to resolve deployment issues. • Develop implementation documentation, operating procedures, and technical runbooks. • Support initial cohort activation and transition the deployed service to ongoing operations. • Identify opportunities to extend the platform through Claude Code, Cowork, APIs, MCP, and custom AI solutions. Required Qualifications • Agentic AI development experience • Vibe coding experience with Claude Code • Complex task automation with Claude Cowork Required Skills and Experience • Master's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience. • Experience implementing enterprise SaaS platforms, cloud services, or identity-integrated applications. • Strong understanding of Identity and Access Management (IAM). • Experience configuring SSO using SAML, OAuth 2.0, or OpenID Connect. • Experience with SCIM provisioning and user lifecycle management. • Experience with enterprise security controls, access policies, and security review processes. • Understanding of APIs, network connectivity, and enterprise integration patterns. • Familiarity with at least one major cloud platform such as AWS, Microsoft Azure, or Google Cloud. • Strong troubleshooting, documentation, and technical diagnostic skills. • Experience working directly with enterprise IT and security organizations. Preferred Qualifications • Experience implementing Anthropic services or comparable enterprise AI platforms. • Experience with Model Context Protocol (MCP) servers, clients, or connectors. • Familiarity with Claude Code, Cowork, Anthropic APIs, and enterprise AI administration. • Experience with security governance, compliance, and risk-management processes. • Knowledge of enterprise architecture, API security, and integration patterns. • Consulting or customer-facing delivery experience. • Software engineering experience with Python, TypeScript, REST APIs, or cloud-native services. Key Competencies • Identity and access management • Enterprise integration • Secure platform deployment • Technical consulting • Cloud and SaaS administration • Governance and compliance • Problem solving and troubleshooting"
Job Description Overview: At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer's and partner's needs and solve their challenges. Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve. You'll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about-locally and globally. Come make an impact every day at Zebra. What We're Looking For: The Cloud AI Engineer, Lead plays a critical role in driving innovation across Zebra's IT Platform Engineering, Cloud Security, and Artificial Intelligence initiatives. Acting as a hands-on technical architect and strategic trailblazer, you will partner with key stakeholders to identify opportunities, translate ideas into actionable solutions, and deliver value through rapid proofs of concept. This role focuses heavily on designing, building, and scaling our next-generation cloud-native AI platforms, AI-powered log intelligence (AIOps), and semantic developer tooling. Location: This is a hybrid position requiring a minimum of three days per week on-site at either our Lincolnshire, IL, or Holtsville, NY office. Essential Duties/Responsabilities: Identify and evaluate emerging innovation opportunities across Platform Engineering and Cloud Infrastructure functions, matching business needs with cutting-edge technology solutions. Conduct comprehensive business and systems analyses, translating complex technical findings into clear user stories, system requirements, and actionable solution concepts. Coordinate and execute Proof of Concepts (PoCs) and hands-on delivery activities to rapidly validate and advance cloud and platform innovation initiatives. Research, analyze, and report on disruptive technologies-such as Generative AI, Machine Learning (ML), Robotic Process Automation (RPA), and Virtual Agents-providing strategic recommendations for corporate adoption. Act as the primary IT Cloud Innovation Liaison, driving cross-functional collaboration and alignment with other innovation and product teams across Zebra. Plan, coordinate, and facilitate structured ideation workshops, fostering a culture of collaborative brainstorming and innovative problem-solving. Serve as an active Innovation Evangelist within IT and the broader enterprise, promoting modern engineering methodologies and pushing the boundaries of cloud-native possibilities. Track, analyze, and report key performance indicators (KPIs), ensuring leadership has complete visibility into the progress, and business outcomes of all innovation initiatives. Establish and maintain a repeatable operating model for cloud-native AI/ML deployment, ensuring all initiatives consistently address pipeline architecture, performance metrics, and compliance guidelines across GCP and Azure. Lead and mentor a high-performing team of cloud and AI platform engineers, guiding their professional evolution toward predictive log analytics, automation (AIOps), and robust cloud data readiness. Translate complex AI governance, cloud security guardrails, and regulatory requirements into practical technical specifications, partnering directly with systems engineers to integrate PII masking and RBAC into automated CI/CD pipelines. Manage roadmap alignment within assigned technology portfolios. Minimum Qualifications: Bachelor's degree in Computer Science, Electronic Engineering, Computer Engineering, or related field. 5+ years experience working on an operations style team (NOC, SOC, MOC, etc.) and troubleshooting networking, service desk, operations center and/or supporting cloud based Infrastructure. Hands-on Google Gemini Enterprise Expertise: Demonstrated experience working with Google Gemini Enterprise, with a proven ability to build and deploy custom agents using the Agent Development Kit (ADK). Multi-Cloud & GenAI Platform Proficiency: Deep familiarity with leading cloud platforms and generative AI solution providers, including Google Cloud Platform (GCP), Azure, OpenAI, and Anthropic. Experience working in a global, heterogeneous, cloud and on-prem environment. Practical knowledge of, or deep technical curiosity to develop, hands-on solutions involving Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and agentic AI patterns (including Model Context Protocol MCP , tool calling, and orchestration frameworks). Expertise in scripting or programming languages (e.g., Python) for automation or testing is a plus; software development background is welcomed. Proven track record of deploying containerized AI solutions using Kubernetes (GKE/AKS), Docker, and robust CI/CD pipelines, backed by verifiable metrics such as high availability, latency reduction, and infrastructure cost optimization. Comprehensive understanding of enterprise cloud security, application/API security, and fine-grained identity systems, with experience integrating PII masking and complex Role-Based Access Control (RBAC) frameworks. Strong software development background with advanced scripting capabilities in Python (or similar languages) to drive automation, infrastructure provisioning (IaC), and automated testing. Active professional-level cloud certifications are highly preferred, such as Google Cloud Professional Cloud Architect, Google Cloud Professional Machine Learning Engineer or AI Engineer Preferred Qualifications Some exposure to AI/ML systems, application security, or API security is a plus. Travel up to 10% Equal Opportunity Employer: Zebra is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability and protected veteran status, or any other basis prohibited by law. If you are an individual with a disability and need assistance in applying for a position, please contact us at . Know Your Rights: - 10/EEOC_KnowYourRights_screen_reader_10_20.pdf Conozca sus Derechos: -_EEOC_KnowYourRightsSp_10_20.pdf We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at . Pay Range: $96,800.00 - $145,200.00 Annual Incentive Compensation: In addition to base pay, Zebra offers this role the opportunity to earn a performance-based annual cash incentive, at a target equal to 10% of base pay, in accordance with the terms of the applicable incentive plan. Zebra Total Rewards: Zebra Total Rewards includes more than just pay and is structured to meet the needs of our changing global business and evolving talent. We are committed to providing our employees with a benefits program that is comprehensive and competitive - including healthcare, wellness, inclusion networks, and continued learning and development offerings. We offer community service days, in addition to the traditional insurances, compensation, parental leave, employee assistance program and paid time off offerings depending on the country where you work. Salary offered will vary depending on your location, job-related skills, knowledge, and experience. Additionally, all Zebra roles are eligible for cash incentive programs. For example, sales roles have additional opportunity to earn substantial variable compensation tied to quota achievement. In most other roles, the Zebra annual cash incentive program links Company and individual performance together. Some roles may also be eligible for long-term incentive equity awards. Benefits: We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success. Job Posting Statement: To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department. AI Technology Statement: Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However . click apply for full job details
11/14/2026
Full time
Job Description Overview: At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer's and partner's needs and solve their challenges. Being part of Zebra Nation means you are seen, heard, valued, and respected. Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve. You'll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about-locally and globally. Come make an impact every day at Zebra. What We're Looking For: The Cloud AI Engineer, Lead plays a critical role in driving innovation across Zebra's IT Platform Engineering, Cloud Security, and Artificial Intelligence initiatives. Acting as a hands-on technical architect and strategic trailblazer, you will partner with key stakeholders to identify opportunities, translate ideas into actionable solutions, and deliver value through rapid proofs of concept. This role focuses heavily on designing, building, and scaling our next-generation cloud-native AI platforms, AI-powered log intelligence (AIOps), and semantic developer tooling. Location: This is a hybrid position requiring a minimum of three days per week on-site at either our Lincolnshire, IL, or Holtsville, NY office. Essential Duties/Responsabilities: Identify and evaluate emerging innovation opportunities across Platform Engineering and Cloud Infrastructure functions, matching business needs with cutting-edge technology solutions. Conduct comprehensive business and systems analyses, translating complex technical findings into clear user stories, system requirements, and actionable solution concepts. Coordinate and execute Proof of Concepts (PoCs) and hands-on delivery activities to rapidly validate and advance cloud and platform innovation initiatives. Research, analyze, and report on disruptive technologies-such as Generative AI, Machine Learning (ML), Robotic Process Automation (RPA), and Virtual Agents-providing strategic recommendations for corporate adoption. Act as the primary IT Cloud Innovation Liaison, driving cross-functional collaboration and alignment with other innovation and product teams across Zebra. Plan, coordinate, and facilitate structured ideation workshops, fostering a culture of collaborative brainstorming and innovative problem-solving. Serve as an active Innovation Evangelist within IT and the broader enterprise, promoting modern engineering methodologies and pushing the boundaries of cloud-native possibilities. Track, analyze, and report key performance indicators (KPIs), ensuring leadership has complete visibility into the progress, and business outcomes of all innovation initiatives. Establish and maintain a repeatable operating model for cloud-native AI/ML deployment, ensuring all initiatives consistently address pipeline architecture, performance metrics, and compliance guidelines across GCP and Azure. Lead and mentor a high-performing team of cloud and AI platform engineers, guiding their professional evolution toward predictive log analytics, automation (AIOps), and robust cloud data readiness. Translate complex AI governance, cloud security guardrails, and regulatory requirements into practical technical specifications, partnering directly with systems engineers to integrate PII masking and RBAC into automated CI/CD pipelines. Manage roadmap alignment within assigned technology portfolios. Minimum Qualifications: Bachelor's degree in Computer Science, Electronic Engineering, Computer Engineering, or related field. 5+ years experience working on an operations style team (NOC, SOC, MOC, etc.) and troubleshooting networking, service desk, operations center and/or supporting cloud based Infrastructure. Hands-on Google Gemini Enterprise Expertise: Demonstrated experience working with Google Gemini Enterprise, with a proven ability to build and deploy custom agents using the Agent Development Kit (ADK). Multi-Cloud & GenAI Platform Proficiency: Deep familiarity with leading cloud platforms and generative AI solution providers, including Google Cloud Platform (GCP), Azure, OpenAI, and Anthropic. Experience working in a global, heterogeneous, cloud and on-prem environment. Practical knowledge of, or deep technical curiosity to develop, hands-on solutions involving Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, and agentic AI patterns (including Model Context Protocol MCP , tool calling, and orchestration frameworks). Expertise in scripting or programming languages (e.g., Python) for automation or testing is a plus; software development background is welcomed. Proven track record of deploying containerized AI solutions using Kubernetes (GKE/AKS), Docker, and robust CI/CD pipelines, backed by verifiable metrics such as high availability, latency reduction, and infrastructure cost optimization. Comprehensive understanding of enterprise cloud security, application/API security, and fine-grained identity systems, with experience integrating PII masking and complex Role-Based Access Control (RBAC) frameworks. Strong software development background with advanced scripting capabilities in Python (or similar languages) to drive automation, infrastructure provisioning (IaC), and automated testing. Active professional-level cloud certifications are highly preferred, such as Google Cloud Professional Cloud Architect, Google Cloud Professional Machine Learning Engineer or AI Engineer Preferred Qualifications Some exposure to AI/ML systems, application security, or API security is a plus. Travel up to 10% Equal Opportunity Employer: Zebra is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability and protected veteran status, or any other basis prohibited by law. If you are an individual with a disability and need assistance in applying for a position, please contact us at . Know Your Rights: - 10/EEOC_KnowYourRights_screen_reader_10_20.pdf Conozca sus Derechos: -_EEOC_KnowYourRightsSp_10_20.pdf We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation at . Pay Range: $96,800.00 - $145,200.00 Annual Incentive Compensation: In addition to base pay, Zebra offers this role the opportunity to earn a performance-based annual cash incentive, at a target equal to 10% of base pay, in accordance with the terms of the applicable incentive plan. Zebra Total Rewards: Zebra Total Rewards includes more than just pay and is structured to meet the needs of our changing global business and evolving talent. We are committed to providing our employees with a benefits program that is comprehensive and competitive - including healthcare, wellness, inclusion networks, and continued learning and development offerings. We offer community service days, in addition to the traditional insurances, compensation, parental leave, employee assistance program and paid time off offerings depending on the country where you work. Salary offered will vary depending on your location, job-related skills, knowledge, and experience. Additionally, all Zebra roles are eligible for cash incentive programs. For example, sales roles have additional opportunity to earn substantial variable compensation tied to quota achievement. In most other roles, the Zebra annual cash incentive program links Company and individual performance together. Some roles may also be eligible for long-term incentive equity awards. Benefits: We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success. Job Posting Statement: To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department. AI Technology Statement: Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However . click apply for full job details
Job Description Position Summary We are looking to add to our dynamic team the critical role of Enterprise AI Architect to help turn AI ideas into secure, scalable, production-ready business solutions. This high-visibility role will define the architecture, patterns, and guardrails that help the company adopt AI responsibly and at scale. The ideal candidate is a hands-on solution architect who can translate business needs into practical AI solutions, design agentic and multi-agent architectures, and partner across business, IT, data, cybersecurity, and operations teams. This is a builder role for someone excited to create the enterprise AI playbook in a global manufacturing and technology environment. Why This Role Is Exciting Help define how enterprise AI is built, governed, and scaled. Work on high-value AI use cases that improve real business processes. Shape the company's approach to agents, copilots, AI governance, and responsible adoption. Turn experimentation into measurable enterprise impact. Key Responsibilities AI Strategy & Solution Architecture Define the enterprise AI architecture roadmap, from early use cases to production-ready solutions. Create reusable standards, solution patterns, and best practices for scalable AI delivery. Lead architecture for generative AI, copilots, AI agents, RAG, machine learning, and intelligent workflows. Design agentic and multi-agent solutions with clear controls, escalation paths, and human-in-the-loop checkpoints. Azure AI Platform Leadership Architect solutions using Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Microsoft Fabric, Copilot Studio, Power Platform, and related Microsoft AI services. Define when to use copilots, agents, RAG, automation, custom APIs, or third-party AI tools. Evaluate and integrate AI capabilities from outside the Azure ecosystem, including platforms and models from providers such as OpenAI, Anthropic, Google, and others. Design hybrid AI patterns for manufacturing and operational environments that cannot be fully cloud-native. Enterprise Data & Systems Integration Ground AI solutions in trusted enterprise data, including ERP, SQL Server applications, and manufacturing/OT systems. Define secure data pipelines, APIs, connectors, and integration patterns using standards such as MCP and A2A where appropriate. Cross-Functional Collaboration Partner with business leaders, cybersecurity, infrastructure, data, and development teams to deliver secure, scalable AI solutions. Prioritize AI opportunities based on business value, feasibility, risk, and adoption potential. Agile Delivery Leadership Provide technical leadership across Agile delivery teams, including onshore and offshore resources. Guide AI initiatives from concept through production deployment and support. AI Governance, Risk & Compliance Establish responsible AI, security, compliance, and governance standards for production AI solutions. Define ALM, LLMOps/MLOps, monitoring, versioning, telemetry, and model evaluation practices. Protect AI models and data workflows through access controls, audit trails, data residency, and prompt-injection safeguards. AI Cost Governance (FinOps) Monitor AI compute, API, and cloud costs. Conduct ROI analysis and define success metrics for AI-powered solutions. Required Qualifications Experience 5+ years in solution, cloud, or enterprise architecture. 3+ years designing AI, machine learning, generative AI, or agentic AI solutions. Hands-on experience with Microsoft Azure and Azure AI services. Experience integrating AI with enterprise systems, ERP, manufacturing, or operational data is a plus. Experience leading Agile teams and globally distributed development resources. Technical Skills Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Microsoft Fabric, Copilot Studio, Power Platform. LLMs, RAG, AI agents, prompt engineering, grounding, evaluation, telemetry, and human-in-the-loop patterns. Ability to compare and select fit-for-purpose AI platforms, models, and tools across Microsoft and non-Microsoft ecosystems. MCP, A2A, secure APIs, connectors, cloud architecture, and enterprise integration patterns. Security, identity, governance, MLOps/LLMOps, and regulated-environment awareness. Preferred Certifications Microsoft Certified: Azure Solutions Architect Expert. Microsoft Certified: Azure AI Engineer Associate (or equivalent GenAI/ML certification). Soft Skills Strong communicator who can explain AI concepts to technical and non-technical audiences. Collaborative partner with strong stakeholder management skills. Practical, outcome-focused problem solver who can balance innovation with governance. EEO - M/F/D/V
11/14/2026
Full time
Job Description Position Summary We are looking to add to our dynamic team the critical role of Enterprise AI Architect to help turn AI ideas into secure, scalable, production-ready business solutions. This high-visibility role will define the architecture, patterns, and guardrails that help the company adopt AI responsibly and at scale. The ideal candidate is a hands-on solution architect who can translate business needs into practical AI solutions, design agentic and multi-agent architectures, and partner across business, IT, data, cybersecurity, and operations teams. This is a builder role for someone excited to create the enterprise AI playbook in a global manufacturing and technology environment. Why This Role Is Exciting Help define how enterprise AI is built, governed, and scaled. Work on high-value AI use cases that improve real business processes. Shape the company's approach to agents, copilots, AI governance, and responsible adoption. Turn experimentation into measurable enterprise impact. Key Responsibilities AI Strategy & Solution Architecture Define the enterprise AI architecture roadmap, from early use cases to production-ready solutions. Create reusable standards, solution patterns, and best practices for scalable AI delivery. Lead architecture for generative AI, copilots, AI agents, RAG, machine learning, and intelligent workflows. Design agentic and multi-agent solutions with clear controls, escalation paths, and human-in-the-loop checkpoints. Azure AI Platform Leadership Architect solutions using Azure AI Foundry, Azure OpenAI, Azure Machine Learning, Microsoft Fabric, Copilot Studio, Power Platform, and related Microsoft AI services. Define when to use copilots, agents, RAG, automation, custom APIs, or third-party AI tools. Evaluate and integrate AI capabilities from outside the Azure ecosystem, including platforms and models from providers such as OpenAI, Anthropic, Google, and others. Design hybrid AI patterns for manufacturing and operational environments that cannot be fully cloud-native. Enterprise Data & Systems Integration Ground AI solutions in trusted enterprise data, including ERP, SQL Server applications, and manufacturing/OT systems. Define secure data pipelines, APIs, connectors, and integration patterns using standards such as MCP and A2A where appropriate. Cross-Functional Collaboration Partner with business leaders, cybersecurity, infrastructure, data, and development teams to deliver secure, scalable AI solutions. Prioritize AI opportunities based on business value, feasibility, risk, and adoption potential. Agile Delivery Leadership Provide technical leadership across Agile delivery teams, including onshore and offshore resources. Guide AI initiatives from concept through production deployment and support. AI Governance, Risk & Compliance Establish responsible AI, security, compliance, and governance standards for production AI solutions. Define ALM, LLMOps/MLOps, monitoring, versioning, telemetry, and model evaluation practices. Protect AI models and data workflows through access controls, audit trails, data residency, and prompt-injection safeguards. AI Cost Governance (FinOps) Monitor AI compute, API, and cloud costs. Conduct ROI analysis and define success metrics for AI-powered solutions. Required Qualifications Experience 5+ years in solution, cloud, or enterprise architecture. 3+ years designing AI, machine learning, generative AI, or agentic AI solutions. Hands-on experience with Microsoft Azure and Azure AI services. Experience integrating AI with enterprise systems, ERP, manufacturing, or operational data is a plus. Experience leading Agile teams and globally distributed development resources. Technical Skills Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Microsoft Fabric, Copilot Studio, Power Platform. LLMs, RAG, AI agents, prompt engineering, grounding, evaluation, telemetry, and human-in-the-loop patterns. Ability to compare and select fit-for-purpose AI platforms, models, and tools across Microsoft and non-Microsoft ecosystems. MCP, A2A, secure APIs, connectors, cloud architecture, and enterprise integration patterns. Security, identity, governance, MLOps/LLMOps, and regulated-environment awareness. Preferred Certifications Microsoft Certified: Azure Solutions Architect Expert. Microsoft Certified: Azure AI Engineer Associate (or equivalent GenAI/ML certification). Soft Skills Strong communicator who can explain AI concepts to technical and non-technical audiences. Collaborative partner with strong stakeholder management skills. Practical, outcome-focused problem solver who can balance innovation with governance. EEO - M/F/D/V
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 Job Title: GenAI Architect Location: New York City, NY (Onsite/Local Candidates Preferred) Experience: 10+ Years Visa: Open to All Visa Types Job Summary: We are seeking an experienced GenAI Architect with 10+ years of overall experience to design, architect, and lead the delivery of enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, and cloud-based AI architectures. The candidate will be responsible for translating business requirements into scalable, secure, and production-ready AI solutions while collaborating closely with business stakeholders, data scientists, and engineering teams. Key Responsibilities: Design and architect enterprise-grade Generative AI solutions leveraging LLMs, RAG pipelines, and agentic AI frameworks. Lead the development and implementation of scalable AI applications and intelligent automation solutions. Architect end-to-end RAG solutions, including document ingestion, chunking, embedding generation, vector databases, retrieval, and response generation. Design and implement agentic workflows using tools, APIs, orchestration frameworks, and multi-agent architectures. Evaluate and integrate LLM models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems. Leverage cloud platforms such as AWS, Azure, or GCP to build and deploy enterprise AI solutions. Establish best practices for prompt engineering, context management, model evaluation, performance optimization, and LLM observability. Ensure AI solutions meet enterprise requirements for security, scalability, governance, compliance, and responsible AI. Collaborate with business stakeholders and technical teams to identify AI opportunities and translate business use cases into technical architectures. Provide technical leadership, architecture guidance, and mentorship to engineering teams throughout the development lifecycle. Required Technical Skills: 10+ years of overall experience in software engineering, solution architecture, AI/ML, or related technology domains. Strong hands-on experience designing and implementing Generative AI and LLM-based applications. Extensive experience with RAG architecture, vector databases, embeddings, semantic search, and knowledge retrieval systems. Strong understanding of Agentic AI, AI agents, multi-agent systems, and tool/function calling. Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar. Proficiency in Python and experience developing enterprise-grade applications and APIs. Experience working with LLM providers such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs. Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform. Knowledge of vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus, or Chroma. Understanding of LLMOps, model deployment, monitoring, evaluation, and optimization. Experience with enterprise security, data privacy, access controls, and responsible AI practices. Preferred Qualifications: Experience architecting and delivering enterprise-scale GenAI solutions from concept to production. Knowledge of Kubernetes, Docker, microservices, and CI/CD pipelines. Experience with fine-tuning, model customization, and prompt optimization. Familiarity with AI governance, guardrails, hallucination mitigation, and responsible AI implementation. Excellent communication, stakeholder management, and technical leadership skills.
11/14/2026
Full time
Job Description Job Title: GenAI Architect Location: New York City, NY (Onsite/Local Candidates Preferred) Experience: 10+ Years Visa: Open to All Visa Types Job Summary: We are seeking an experienced GenAI Architect with 10+ years of overall experience to design, architect, and lead the delivery of enterprise-grade Generative AI solutions. The ideal candidate will have strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI workflows, and cloud-based AI architectures. The candidate will be responsible for translating business requirements into scalable, secure, and production-ready AI solutions while collaborating closely with business stakeholders, data scientists, and engineering teams. Key Responsibilities: Design and architect enterprise-grade Generative AI solutions leveraging LLMs, RAG pipelines, and agentic AI frameworks. Lead the development and implementation of scalable AI applications and intelligent automation solutions. Architect end-to-end RAG solutions, including document ingestion, chunking, embedding generation, vector databases, retrieval, and response generation. Design and implement agentic workflows using tools, APIs, orchestration frameworks, and multi-agent architectures. Evaluate and integrate LLM models from providers such as OpenAI, Anthropic, Google, and open-source ecosystems. Leverage cloud platforms such as AWS, Azure, or GCP to build and deploy enterprise AI solutions. Establish best practices for prompt engineering, context management, model evaluation, performance optimization, and LLM observability. Ensure AI solutions meet enterprise requirements for security, scalability, governance, compliance, and responsible AI. Collaborate with business stakeholders and technical teams to identify AI opportunities and translate business use cases into technical architectures. Provide technical leadership, architecture guidance, and mentorship to engineering teams throughout the development lifecycle. Required Technical Skills: 10+ years of overall experience in software engineering, solution architecture, AI/ML, or related technology domains. Strong hands-on experience designing and implementing Generative AI and LLM-based applications. Extensive experience with RAG architecture, vector databases, embeddings, semantic search, and knowledge retrieval systems. Strong understanding of Agentic AI, AI agents, multi-agent systems, and tool/function calling. Experience with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar. Proficiency in Python and experience developing enterprise-grade applications and APIs. Experience working with LLM providers such as OpenAI, Azure OpenAI, Anthropic, Gemini, or open-source LLMs. Strong experience with at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud Platform. Knowledge of vector databases such as Pinecone, Azure AI Search, FAISS, Weaviate, Milvus, or Chroma. Understanding of LLMOps, model deployment, monitoring, evaluation, and optimization. Experience with enterprise security, data privacy, access controls, and responsible AI practices. Preferred Qualifications: Experience architecting and delivering enterprise-scale GenAI solutions from concept to production. Knowledge of Kubernetes, Docker, microservices, and CI/CD pipelines. Experience with fine-tuning, model customization, and prompt optimization. Familiarity with AI governance, guardrails, hallucination mitigation, and responsible AI implementation. Excellent communication, stakeholder management, and technical leadership skills.
Job Description AI ML Engineer Intern - Winter / Spring 2027 (Master's or PhD) Salary: $25 - 30/ hr About Akoncagua AI Akoncagua AI builds domain-specialized AI systems for technically demanding industries. Our work includes LLMs, multimodal AI, agentic automation, RAG, evaluation, and production AI infrastructure. We are seeking an AI Automation Engineer Intern to help build secure, reliable AI agents and automated workflows for accounting and enterprise finance. What you'll work on Build and improve LLM agent workflows for document intake, classification, and transaction coding Develop document-intelligence pipelines for invoices, receipts, contracts, and financial statements Implement retrieval over accounting policies, vendor records, and historical transactions Write evaluation harnesses that measure extraction accuracy, classification quality, and end-to-end workflow outcomes Add tracing and observability for prompts, tool calls, failures, latency, and cost Integrate agents with accounting platforms, databases, and internal APIs Required qualifications Currently enrolled in a Master's or PhD program in Computer Science, AI/ML, or a related technical field, or equivalent practical experience Strong Python skills, plus solid fundamentals in data structures, debugging, and testing Experience building LLM-based applications, whether through coursework, research, personal projects, or internships Familiarity with at least one agent framework such as LangGraph, AutoGen/AG2, Semantic Kernel, or the OpenAI Agents SDK Working knowledge of RAG and vector databases Comfortable with Docker and version control in a collaborative codebase Preferred qualifications Experience with MCP or similar tool-integration standards Experience with n8n, Zapier, Make, or event-driven automation Exposure to FastAPI, PostgreSQL, pgvector, or Kubernetes Interest in or exposure to accounting concepts such as double-entry bookkeeping, journal entries, reconciliations, or approval controls Awareness of prompt-injection risks, least-privilege design, and secrets management Strong understanding of multi-GPU Linux server environments, with hands-on experience configuring, managing, and effectively utilizing GPU resources. Open-source contributions or publications at AI conferences How we work We care about researchers and engineers who understand and can defend the design decisions in their code. AI coding tools are welcome here, but you should be able to explain why a system works the way it does, what evidence supports it, and where it breaks. Our work connects model research with the systems required to run it. You will have room to explore new ideas, but you will also be expected to build working implementations, measure them carefully, and communicate their limitations clearly.
11/14/2026
Full time
Job Description AI ML Engineer Intern - Winter / Spring 2027 (Master's or PhD) Salary: $25 - 30/ hr About Akoncagua AI Akoncagua AI builds domain-specialized AI systems for technically demanding industries. Our work includes LLMs, multimodal AI, agentic automation, RAG, evaluation, and production AI infrastructure. We are seeking an AI Automation Engineer Intern to help build secure, reliable AI agents and automated workflows for accounting and enterprise finance. What you'll work on Build and improve LLM agent workflows for document intake, classification, and transaction coding Develop document-intelligence pipelines for invoices, receipts, contracts, and financial statements Implement retrieval over accounting policies, vendor records, and historical transactions Write evaluation harnesses that measure extraction accuracy, classification quality, and end-to-end workflow outcomes Add tracing and observability for prompts, tool calls, failures, latency, and cost Integrate agents with accounting platforms, databases, and internal APIs Required qualifications Currently enrolled in a Master's or PhD program in Computer Science, AI/ML, or a related technical field, or equivalent practical experience Strong Python skills, plus solid fundamentals in data structures, debugging, and testing Experience building LLM-based applications, whether through coursework, research, personal projects, or internships Familiarity with at least one agent framework such as LangGraph, AutoGen/AG2, Semantic Kernel, or the OpenAI Agents SDK Working knowledge of RAG and vector databases Comfortable with Docker and version control in a collaborative codebase Preferred qualifications Experience with MCP or similar tool-integration standards Experience with n8n, Zapier, Make, or event-driven automation Exposure to FastAPI, PostgreSQL, pgvector, or Kubernetes Interest in or exposure to accounting concepts such as double-entry bookkeeping, journal entries, reconciliations, or approval controls Awareness of prompt-injection risks, least-privilege design, and secrets management Strong understanding of multi-GPU Linux server environments, with hands-on experience configuring, managing, and effectively utilizing GPU resources. Open-source contributions or publications at AI conferences How we work We care about researchers and engineers who understand and can defend the design decisions in their code. AI coding tools are welcome here, but you should be able to explain why a system works the way it does, what evidence supports it, and where it breaks. Our work connects model research with the systems required to run it. You will have room to explore new ideas, but you will also be expected to build working implementations, measure them carefully, and communicate their limitations clearly.
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
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Software Applications Engineer Description - Fort Collins, Colorado SPONSORSHIP : This opportunity is intended for conversion to a full-time role that will not offer work authorization sponsorship in the future (full-time conversion pending performance evaluation post internship and available headcount). Interested candidates must be currently eligible to work in the US AND must not require work authorization sponsorship in the future. HP, Inc. will not provide any assistance or sign documentation in support of immigration sponsorship including Curricular Practical Training (CPT) or Optional Practical Training (OPT). About Us Innovation is in HP's DNA. From our origins in a Palo Alto garage in 1939, to our current position as one of the world's leading technology companies, HP has grown to become a leader in technology and corporate culture, inspiring innovators, and entrepreneurs around the globe. HP brings together a portfolio that spans printing, personal computing, software, and services to serve more than 1 billion customers in over 170 countries. We are committed to fostering a diverse and inclusive workplace that attracts exceptional talent and to supporting our employees to succeed at all levels. We dream in over 35 languages and share one mission: to engineer experiences that amaze. The Team: ACS (Advanced Compute & Solutions) is seeking a motivated Software Engineer who is eager to learn and grow in a collaborative, customer-focused environment. The ideal candidate will work closely with senior engineers and cross-functional teams to support technical solutions and customer engagements. You should be comfortable learning and explain technical concepts to both technical and non-technical audiences, collaborate with internal teams, business partners, and contribute to the development and implementation of innovative solutions. Responsibilities: Help build secure new solutions and enhance existing features in our applications. Support development, testing, and deployment of identity services and integrations with external identity providers. Work with senior engineers to troubleshoot and harden authentication flows. Use AI coding assistants and agentic tools to speed up development, testing, and documentation, and review their output for correctness and security. Assist with AI-enabled automation and secure integrations with AI services. Contribute to documentation and best practices across our identity systems. Education and Experience Required : Has completed or is in the process of completing a university degree or higher (bachelor's degree or equivalent) Has completed the degree prior to the start date Has no more than 24 months of prior work experience professionally related to the graduate hire requisition they are applying to (not including internships, teaching assistance, research work, or military experience) No more than 12 months since graduation from a university program Able to obtain work authorization in the United States without requiring sponsorship in the future. Preferred Majors: Bachelor's degree in Computer Science, Data Science, or a related field (or equivalent experience). Preferred Knowledge and Skills: Programming experience in Python, Java, Go, or C++. Basic understanding of REST APIs, HTTP, JWTs, and authentication flows. Foundational knowledge of OAuth 2.0, OpenID Connect (OIDC), and SSO. Exposure to security fundamentals such as TLS, certificates, and firewalls. Hands-on use of AI tools (e.g., Claude, GitHub Copilot, ChatGPT) for coding or projects, plus awareness of AI security risks like prompt injection and data leakage. Strong communication skills and comfort working on a collaborative Agile team. Internship, co-op, or class project involving authentication or identity provider integration. Experience building with LLM APIs, or securing access for AI agents and tools (e.g., OAuth for MCP servers) - this one is an extreme plus! Show us your code, your applications, your github! Familiarity with Microsoft Entra (Azure AD), including app registrations and conditional access. Coursework or certifications in IAM, cloud, or AI (e.g., Microsoft SC-900, AZ-900). We are looking for visionaries who are ready to make an impact on the way the world works. At HP, the future is yours to create. Thanks for taking the time to review our job, if you think it is a match to your knowledge and interests please apply today- we are eager to learn more about you. HP is an equal opportunity employer: Job Posting Expiration Date: 1/3/2027 The pay range for this role is $65,600 to $101,000 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Explore HP Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
11/14/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Software Applications Engineer Description - Fort Collins, Colorado SPONSORSHIP : This opportunity is intended for conversion to a full-time role that will not offer work authorization sponsorship in the future (full-time conversion pending performance evaluation post internship and available headcount). Interested candidates must be currently eligible to work in the US AND must not require work authorization sponsorship in the future. HP, Inc. will not provide any assistance or sign documentation in support of immigration sponsorship including Curricular Practical Training (CPT) or Optional Practical Training (OPT). About Us Innovation is in HP's DNA. From our origins in a Palo Alto garage in 1939, to our current position as one of the world's leading technology companies, HP has grown to become a leader in technology and corporate culture, inspiring innovators, and entrepreneurs around the globe. HP brings together a portfolio that spans printing, personal computing, software, and services to serve more than 1 billion customers in over 170 countries. We are committed to fostering a diverse and inclusive workplace that attracts exceptional talent and to supporting our employees to succeed at all levels. We dream in over 35 languages and share one mission: to engineer experiences that amaze. The Team: ACS (Advanced Compute & Solutions) is seeking a motivated Software Engineer who is eager to learn and grow in a collaborative, customer-focused environment. The ideal candidate will work closely with senior engineers and cross-functional teams to support technical solutions and customer engagements. You should be comfortable learning and explain technical concepts to both technical and non-technical audiences, collaborate with internal teams, business partners, and contribute to the development and implementation of innovative solutions. Responsibilities: Help build secure new solutions and enhance existing features in our applications. Support development, testing, and deployment of identity services and integrations with external identity providers. Work with senior engineers to troubleshoot and harden authentication flows. Use AI coding assistants and agentic tools to speed up development, testing, and documentation, and review their output for correctness and security. Assist with AI-enabled automation and secure integrations with AI services. Contribute to documentation and best practices across our identity systems. Education and Experience Required : Has completed or is in the process of completing a university degree or higher (bachelor's degree or equivalent) Has completed the degree prior to the start date Has no more than 24 months of prior work experience professionally related to the graduate hire requisition they are applying to (not including internships, teaching assistance, research work, or military experience) No more than 12 months since graduation from a university program Able to obtain work authorization in the United States without requiring sponsorship in the future. Preferred Majors: Bachelor's degree in Computer Science, Data Science, or a related field (or equivalent experience). Preferred Knowledge and Skills: Programming experience in Python, Java, Go, or C++. Basic understanding of REST APIs, HTTP, JWTs, and authentication flows. Foundational knowledge of OAuth 2.0, OpenID Connect (OIDC), and SSO. Exposure to security fundamentals such as TLS, certificates, and firewalls. Hands-on use of AI tools (e.g., Claude, GitHub Copilot, ChatGPT) for coding or projects, plus awareness of AI security risks like prompt injection and data leakage. Strong communication skills and comfort working on a collaborative Agile team. Internship, co-op, or class project involving authentication or identity provider integration. Experience building with LLM APIs, or securing access for AI agents and tools (e.g., OAuth for MCP servers) - this one is an extreme plus! Show us your code, your applications, your github! Familiarity with Microsoft Entra (Azure AD), including app registrations and conditional access. Coursework or certifications in IAM, cloud, or AI (e.g., Microsoft SC-900, AZ-900). We are looking for visionaries who are ready to make an impact on the way the world works. At HP, the future is yours to create. Thanks for taking the time to review our job, if you think it is a match to your knowledge and interests please apply today- we are eager to learn more about you. HP is an equal opportunity employer: Job Posting Expiration Date: 1/3/2027 The pay range for this role is $65,600 to $101,000 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Explore HP Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
This job is with Invesco, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About Invesco As one of the world's leading independent global investment firms, Invesco is dedicated to rethinking possibilities for our clients. By delivering the combined power of our distinctive investment management capabilities, we provide a wide range of investment strategies and vehicles to our clients around the world. If you're looking for challenging work, intelligent colleagues, and exposure across a global footprint, come explore your potential at Invesco. What's in it for you? Our people are at the ver y core of our success. Invesco employees get more out of life through our comprehensive compensation and benefit offerings including: Flexible paid time off Hybrid work schedule 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution Health & wellbeing benefits Parental Leave benefits Employee stock purchase plan Job Description About the Team: The Strategy, Innovation & Planning (SIP) team serves as Invesco's central AI hub, focused on advancing innovation and delivering impactful AI solutions across the firm. Our team is focused on rapid experimentation using new AI tools and technologies to solve business problems. We are focused on using various agentic frameworks and building business-sponsored GenAI use cases that drive operational efficiency. Beyond product development, SIP actively fosters AI adoption across Invesco through initiatives such as AI/ML Meetups, hackathons, and cross-team collaborations. About the Role: As Software Engineer on the SIP team, you will help design, build, and scale next-generation AI applications that solve complex business problems. You will work in a highly collaborative, agile environment with a startup mindset-focused on rapid experimentation, continuous learning, and hands-on engineering. This role is designed for a creative technologist who views AI tools (like GitHub Copilot, Cursor, or LLM APIs) or Agentic Frameworks (Microsoft Copilot Studio, AgentCore/Strands, LangGraph etc.) as fundamental to their workflow, enabling them to contribute directly to the future of AI at Invesco. Responsibilities of the Role: Collaborating with data scientists, data engineers, and investment professionals to build innovative AI-based tools using structured and alternate data sources. Rapidly prototyping new and innovative solutions alongside experienced developers, using AI-assisted coding to accelerate the "idea-to-MVP" cycle. Developing and refining Invesco's Generative AI platform by creating system prompts, implementing agentic workflows and LLM-integrated features. Coding and delivering cloud-native microservices and micro-UI components that integrate seamlessly with AI orchestration layers. Building validations, evaluations and guardrails on selected agent frameworks for custom agents built for various business use cases Applying "AI-first" engineering principles to find creative solutions to the unique architectural challenges encountered when scaling agentic systems. Working at speed to show measurable value per sprint, maintaining high code quality through modern automation and testing. Requirements of the Role: Creative Problem Solver: 0-2 years of experience with a portfolio of projects (professional or personal) that demonstrate an ability to build functional, creative web applications. Modern Tech Stack: Foundational proficiency in Python (for AI/Backend) and TypeScript/React (for Frontend). AI Native Workflow: High level of comfort using AI coding assistants and LLMs to debug, document, and write boilerplate code efficiently. Architectural Curiosity: Exposure to (or a strong desire to learn) LangGraph, LangChain, and agentic design patterns. Cloud & DevOps Foundations: Familiarity with containerized environments (Docker), Git version control, and basic cloud concepts (AWS or Azure). Agile Mindset: A proactive learner who thrives in a fast-paced, value-driven environment and is comfortable experimenting with emerging technologies. Full Time / Part Time Full time Worker Type Employee Job Exempt (Yes / No) Yes Workplace Model Pursuant to Invesco's Workplace Policy, employees are expected to comply with the firm's most current workplace model, which as of October 1, 2025, includes spending at least four full days each week working in an Invesco office. This reflects our belief that spending time together in the office helps us build stronger relationships, collaborate more easily, and support each other's growth and development. The above information on this description has been designed to indicate the general nature and level of work performed by employees within this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job. The job holder may be required to perform other duties as deemed appropriate by their manager from time to time. Invesco's culture of inclusivity and its commitment to diversity in the workplace are demonstrated through our people practices. We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender, gender identity, sexual orientation, marital status, national origin, citizenship status, disability, age, or veteran status. Our equal opportunity employment efforts comply with all applicable U.S. state and federal laws governing non-discrimination in employment.
11/13/2026
Full time
This job is with Invesco, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About Invesco As one of the world's leading independent global investment firms, Invesco is dedicated to rethinking possibilities for our clients. By delivering the combined power of our distinctive investment management capabilities, we provide a wide range of investment strategies and vehicles to our clients around the world. If you're looking for challenging work, intelligent colleagues, and exposure across a global footprint, come explore your potential at Invesco. What's in it for you? Our people are at the ver y core of our success. Invesco employees get more out of life through our comprehensive compensation and benefit offerings including: Flexible paid time off Hybrid work schedule 401(K) matching of 100% up to the first 6% with a discretionary supplemental contribution Health & wellbeing benefits Parental Leave benefits Employee stock purchase plan Job Description About the Team: The Strategy, Innovation & Planning (SIP) team serves as Invesco's central AI hub, focused on advancing innovation and delivering impactful AI solutions across the firm. Our team is focused on rapid experimentation using new AI tools and technologies to solve business problems. We are focused on using various agentic frameworks and building business-sponsored GenAI use cases that drive operational efficiency. Beyond product development, SIP actively fosters AI adoption across Invesco through initiatives such as AI/ML Meetups, hackathons, and cross-team collaborations. About the Role: As Software Engineer on the SIP team, you will help design, build, and scale next-generation AI applications that solve complex business problems. You will work in a highly collaborative, agile environment with a startup mindset-focused on rapid experimentation, continuous learning, and hands-on engineering. This role is designed for a creative technologist who views AI tools (like GitHub Copilot, Cursor, or LLM APIs) or Agentic Frameworks (Microsoft Copilot Studio, AgentCore/Strands, LangGraph etc.) as fundamental to their workflow, enabling them to contribute directly to the future of AI at Invesco. Responsibilities of the Role: Collaborating with data scientists, data engineers, and investment professionals to build innovative AI-based tools using structured and alternate data sources. Rapidly prototyping new and innovative solutions alongside experienced developers, using AI-assisted coding to accelerate the "idea-to-MVP" cycle. Developing and refining Invesco's Generative AI platform by creating system prompts, implementing agentic workflows and LLM-integrated features. Coding and delivering cloud-native microservices and micro-UI components that integrate seamlessly with AI orchestration layers. Building validations, evaluations and guardrails on selected agent frameworks for custom agents built for various business use cases Applying "AI-first" engineering principles to find creative solutions to the unique architectural challenges encountered when scaling agentic systems. Working at speed to show measurable value per sprint, maintaining high code quality through modern automation and testing. Requirements of the Role: Creative Problem Solver: 0-2 years of experience with a portfolio of projects (professional or personal) that demonstrate an ability to build functional, creative web applications. Modern Tech Stack: Foundational proficiency in Python (for AI/Backend) and TypeScript/React (for Frontend). AI Native Workflow: High level of comfort using AI coding assistants and LLMs to debug, document, and write boilerplate code efficiently. Architectural Curiosity: Exposure to (or a strong desire to learn) LangGraph, LangChain, and agentic design patterns. Cloud & DevOps Foundations: Familiarity with containerized environments (Docker), Git version control, and basic cloud concepts (AWS or Azure). Agile Mindset: A proactive learner who thrives in a fast-paced, value-driven environment and is comfortable experimenting with emerging technologies. Full Time / Part Time Full time Worker Type Employee Job Exempt (Yes / No) Yes Workplace Model Pursuant to Invesco's Workplace Policy, employees are expected to comply with the firm's most current workplace model, which as of October 1, 2025, includes spending at least four full days each week working in an Invesco office. This reflects our belief that spending time together in the office helps us build stronger relationships, collaborate more easily, and support each other's growth and development. The above information on this description has been designed to indicate the general nature and level of work performed by employees within this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to this job. The job holder may be required to perform other duties as deemed appropriate by their manager from time to time. Invesco's culture of inclusivity and its commitment to diversity in the workplace are demonstrated through our people practices. We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender, gender identity, sexual orientation, marital status, national origin, citizenship status, disability, age, or veteran status. Our equal opportunity employment efforts comply with all applicable U.S. state and federal laws governing non-discrimination in employment.
Date Posted: 2026-10-13 Country: United States of America Location: US-CO-AURORA-S E Hughes Dr BLDG S77 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: TS/SCI - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon's Air & Space Defense Systems (ASDS) strategic business unit (SBU) specializes in multi-domain integrated air and missile defense, advanced sensors, space-based systems, hypersonics, effectors, and cyber solutions. Focused on program execution, business growth and the highest level of customer satisfaction, the ASDS team provides customers with unmatched capabilities of detection and sensing, command and control, and air-to-air, air-to-surface, and surface-to-air munitions to accomplish air, space and missile defense missions. This position is an onsite role in Aurora, CO What You Will Do Lead AI/ML architecture and implementation Design, develop, test, deliver, and maintain software for cutting-edge satellite ground systems. Work with a team of engineers, architects, and leaders in an Agile environment. What You Will Learn A breadth of advanced software technologies and techniques including multi-tiered architectures, AWS web services, and microservice software design. Modern DevSecOps and Continuous Integration/Continuous Delivery techniques. Software lifecycle practices for defense projects. Satellite ground system technologies. Qualifications You Must Have A Bachelor's degree in Science, Technology, Engineering or Mathematics (STEM) and 8 years of prior relevant experience. Experience with agentic and multi-agent AI/ML systems. Experience developing software using Java, Python, and JavaScript. Experience developing satellite planning & scheduling software. Experience with containerization using Docker, Kubernetes, and Kafka. An active and transferable U.S. government issued TS/SCI security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance. Qualifications We Prefer Software development lifecycle experience using the SAFe Agile methodology. Experience with Test Automation, DevSecOps, and CI/CD processes. Experience with tools such as Confluence, Eclipse, Jira, Jenkins, Junit, Kafka, and Spring Boot. What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value, Safety, Trust, Respect, Accountability, Collaboration, and Innovation. Relocation eligible. Relocation assistance is available for this role. Learn More & Apply Now! Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. Location Information: Aurora, CO: As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 107,500 USD - 204,500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
11/13/2026
Full time
Date Posted: 2026-10-13 Country: United States of America Location: US-CO-AURORA-S E Hughes Dr BLDG S77 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: Active and transferable U.S. government issued security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: TS/SCI - Current Security Clearance Status: Active and existing security clearance required on day 1 At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world's most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation and allies defend freedoms and deter aggression, creating a safer, more secure world. Join us and help shape the future of aerospace and defense. Raytheon's Air & Space Defense Systems (ASDS) strategic business unit (SBU) specializes in multi-domain integrated air and missile defense, advanced sensors, space-based systems, hypersonics, effectors, and cyber solutions. Focused on program execution, business growth and the highest level of customer satisfaction, the ASDS team provides customers with unmatched capabilities of detection and sensing, command and control, and air-to-air, air-to-surface, and surface-to-air munitions to accomplish air, space and missile defense missions. This position is an onsite role in Aurora, CO What You Will Do Lead AI/ML architecture and implementation Design, develop, test, deliver, and maintain software for cutting-edge satellite ground systems. Work with a team of engineers, architects, and leaders in an Agile environment. What You Will Learn A breadth of advanced software technologies and techniques including multi-tiered architectures, AWS web services, and microservice software design. Modern DevSecOps and Continuous Integration/Continuous Delivery techniques. Software lifecycle practices for defense projects. Satellite ground system technologies. Qualifications You Must Have A Bachelor's degree in Science, Technology, Engineering or Mathematics (STEM) and 8 years of prior relevant experience. Experience with agentic and multi-agent AI/ML systems. Experience developing software using Java, Python, and JavaScript. Experience developing satellite planning & scheduling software. Experience with containerization using Docker, Kubernetes, and Kafka. An active and transferable U.S. government issued TS/SCI security clearance is required prior to start date. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance. Qualifications We Prefer Software development lifecycle experience using the SAFe Agile methodology. Experience with Test Automation, DevSecOps, and CI/CD processes. Experience with tools such as Confluence, Eclipse, Jira, Jenkins, Junit, Kafka, and Spring Boot. What We Offer Our values drive our actions, behaviors, and performance with a vision for a safer, more connected world. At RTX we value, Safety, Trust, Respect, Accountability, Collaboration, and Innovation. Relocation eligible. Relocation assistance is available for this role. Learn More & Apply Now! Onsite: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. Location Information: Aurora, CO: As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 107,500 USD - 204,500 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Principal Enterprise Integration and Platform Native AI Description - Role Summary We are seeking an exceptional Principal Enterprise Integration & AI to lead HP's enterprise integration and AI architecture at global scale. This role serves as a technical authority, strategic thought leader, and innovation driver , responsible for shaping HP's integration fabric, API economy, and AI enablement strategy across Digital Tech. The Distinguished Engineer will define long-term architecture vision, influence enterprise-wide technology decisions, and ensure scalable, secure, and AI-ready platforms that accelerate business outcomes. This role operates at the intersection of integration, APIs, data, and AI , driving foundational capabilities that power HP's digital transformation and agentic AI future. Key Responsibilities API & AI-First API Strategy and Governance Define and lead HP's AI-first API strategy , ensuring all enterprise APIs are discoverable, reusable, and optimized for machine and agent consumption Institutionalize the API-as-a-Product operating model, with clear ownership, lifecycle governance, and measurable business value Own and enforce enterprise-wide API governance standards, covering design, lifecycle, security, and AI readiness Define and operationalize the AI-Ready API Framework , including automated governance gates to ensure production readiness Enable HP's Unified API & Agentic AI Strategy , positioning APIs as the foundation for enterprise AI adoption Establish standards for emerging integration paradigms, including event-driven architectures and MCP (Model Context Protocol) Platform AI Enablement & Governance Orchestrate AI enablement and adoption across strategic platforms (SAP, ServiceNow, Adobe, MuleSoft, NOVA) Own the enterprise AI/ML governance process, including AI board reviews, privacy, risk, and cybersecurity compliance Evaluate and guide platform-native AI capabilities to ensure alignment with enterprise architecture and compliance requirements Lead cross-functional AI enablement initiatives to drive consistent adoption and measurable business outcomes Align platform AI initiatives with enterprise prioritization frameworks (e.g., Digital AI Nerve Center) Evaluate AI tooling, vendor solutions, and partner ecosystems for alignment with integration and platform strategy Enable AI-driven SDLC adoption for partner ecosystems (e.g., NOVA vendors), including onboarding, compliance, and knowledge integration Lead/ support key tech initiatives Lead evaluation of new and emerging tech, conduct POC, and lay down path for adoption. Lead the EPS AI initiatives through AI/ML review board and cyber approval process. Partner with Applied AI teams for knowledge sharing of Enterprise AI initiatives Coach and mentor teams in their AI journey Improve reuse, reduce duplication, and strengthen governance via API-as-a-product discipline Enable scalable, enterprise-grade AI products (e.g., IBDF, AIOps) delivering measurable business value Qualifications & Experience 10+ years of experience in enterprise architecture, integration, and platform engineering Proven track record defining and implementing enterprise integration strategies and API ecosystems at scale Deep expertise in integration patterns (event-driven, messaging, APIs, microservices) and cloud-native architectures Experience leading AI/ML enablement, governance, and platform integration in large enterprises Strong understanding of enterprise platforms (SAP, ServiceNow, Adobe, MuleSoft) and their AI capabilities Demonstrated ability to influence executive stakeholders and drive cross-functional alignment Recognized as a thought leader and technical authority , with experience mentoring senior architects and engineers Leadership Expectations Act as a trusted advisor to executive leadership on enterprise architecture and AI strategy Drive innovation by identifying emerging technologies and translating them into enterprise capabilities Mentor and elevate the technical community, fostering architectural excellence across HP Represent HP externally with partners, customers, and industry forums as a leader in integration and AI Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. Preferred Certifications Programming Language/s Certification (Java, C++, Python, JavaScript, or similar) Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity Impact & Scope Impacts multiple functions and influences long-term strategic direction across multiple disciplines or areas of HP. Complexity Invents, develops and introduces new methods and techniques that impact multiple disciplines and work groups. Pay & Benefits The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave US benefits overview The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
11/13/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Principal Enterprise Integration and Platform Native AI Description - Role Summary We are seeking an exceptional Principal Enterprise Integration & AI to lead HP's enterprise integration and AI architecture at global scale. This role serves as a technical authority, strategic thought leader, and innovation driver , responsible for shaping HP's integration fabric, API economy, and AI enablement strategy across Digital Tech. The Distinguished Engineer will define long-term architecture vision, influence enterprise-wide technology decisions, and ensure scalable, secure, and AI-ready platforms that accelerate business outcomes. This role operates at the intersection of integration, APIs, data, and AI , driving foundational capabilities that power HP's digital transformation and agentic AI future. Key Responsibilities API & AI-First API Strategy and Governance Define and lead HP's AI-first API strategy , ensuring all enterprise APIs are discoverable, reusable, and optimized for machine and agent consumption Institutionalize the API-as-a-Product operating model, with clear ownership, lifecycle governance, and measurable business value Own and enforce enterprise-wide API governance standards, covering design, lifecycle, security, and AI readiness Define and operationalize the AI-Ready API Framework , including automated governance gates to ensure production readiness Enable HP's Unified API & Agentic AI Strategy , positioning APIs as the foundation for enterprise AI adoption Establish standards for emerging integration paradigms, including event-driven architectures and MCP (Model Context Protocol) Platform AI Enablement & Governance Orchestrate AI enablement and adoption across strategic platforms (SAP, ServiceNow, Adobe, MuleSoft, NOVA) Own the enterprise AI/ML governance process, including AI board reviews, privacy, risk, and cybersecurity compliance Evaluate and guide platform-native AI capabilities to ensure alignment with enterprise architecture and compliance requirements Lead cross-functional AI enablement initiatives to drive consistent adoption and measurable business outcomes Align platform AI initiatives with enterprise prioritization frameworks (e.g., Digital AI Nerve Center) Evaluate AI tooling, vendor solutions, and partner ecosystems for alignment with integration and platform strategy Enable AI-driven SDLC adoption for partner ecosystems (e.g., NOVA vendors), including onboarding, compliance, and knowledge integration Lead/ support key tech initiatives Lead evaluation of new and emerging tech, conduct POC, and lay down path for adoption. Lead the EPS AI initiatives through AI/ML review board and cyber approval process. Partner with Applied AI teams for knowledge sharing of Enterprise AI initiatives Coach and mentor teams in their AI journey Improve reuse, reduce duplication, and strengthen governance via API-as-a-product discipline Enable scalable, enterprise-grade AI products (e.g., IBDF, AIOps) delivering measurable business value Qualifications & Experience 10+ years of experience in enterprise architecture, integration, and platform engineering Proven track record defining and implementing enterprise integration strategies and API ecosystems at scale Deep expertise in integration patterns (event-driven, messaging, APIs, microservices) and cloud-native architectures Experience leading AI/ML enablement, governance, and platform integration in large enterprises Strong understanding of enterprise platforms (SAP, ServiceNow, Adobe, MuleSoft) and their AI capabilities Demonstrated ability to influence executive stakeholders and drive cross-functional alignment Recognized as a thought leader and technical authority , with experience mentoring senior architects and engineers Leadership Expectations Act as a trusted advisor to executive leadership on enterprise architecture and AI strategy Drive innovation by identifying emerging technologies and translating them into enterprise capabilities Mentor and elevate the technical community, fostering architectural excellence across HP Represent HP externally with partners, customers, and industry forums as a leader in integration and AI Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. Preferred Certifications Programming Language/s Certification (Java, C++, Python, JavaScript, or similar) Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) Cross-Org Skills • Effective Communication • Results Orientation • Learning Agility • Digital Fluency • Customer Centricity Impact & Scope Impacts multiple functions and influences long-term strategic direction across multiple disciplines or areas of HP. Complexity Invents, develops and introduces new methods and techniques that impact multiple disciplines and work groups. Pay & Benefits The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave US benefits overview The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Disclaimer This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 15 The Team: Enterprise Technology & Platforms delivers cross-enterprise technology products, services, and capabilities to S&P Global's organizations and employees worldwide. The Developer Experience and Product Enablement function will own and evolve the enterprise product and software development lifecycle toolchain - the agentic PDLC - bringing together platforms, governance, support, productivity insights, and AI-native product management and engineering capabilities. It spans the full path from discovery and customer insight through definition, design, build, release, and in-market measurement, treating product management and engineering as one connected system rather than two adjacent toolsets. The team will operate as an enterprise hub, partnering closely with divisional CTO and product organizations and embedded practitioners to preserve business context while creating a consistent, scalable experience for both builders and the product leaders who direct them. Responsibilities and Impact: Approximately 10,000 developers across S&P Global build software on a common toolchain, and the product managers, designers, and analysts who decide what gets built work alongside them on a second, largely disconnected one. This role owns both and joins them. That toolchain is critical infrastructure for product discovery, software delivery, engineering productivity, security, resilience, and AI-native development. The role will reduce fragmentation and duplication, close the handoff gaps between product intent and shipped software, strengthen governance and support, and make developer and product experience a measurable strategic capability. Set the enterprise Developer Experience and Product Enablement strategy, product vision, roadmap, operating model, and investment priorities in partnership with the CIO leadership team, divisional CTOs, divisional heads of product, and other senior technology and product leaders. Own the full lifecycle of enterprise software development platforms and tools, including source code management, code collaboration, CI/CD, build engineering, developer environments, code quality and scanning, cloud development infrastructure, and related integrations. Own the full lifecycle of enterprise product management platforms and tools, including customer and market research repositories, idea intake and opportunity assessment, roadmapping and portfolio planning, requirements and specification authoring, design and prototyping, work management and backlog tooling, experimentation and feature management, product analytics, and voice-of-customer and feedback aggregation. Connect the two halves into a single agentic PDLC, establishing the traceable thread from customer insight to opportunity, specification, design, commit, release, and in-market outcome, so that product intent, engineering work, and measured impact reconcile in one system of record rather than in status decks. Manage the toolchain as a coherent portfolio of enterprise products, with clear customer outcomes, service levels, adoption goals, cost transparency, platform health measures, and accountable product ownership. Build a trusted partnership model with divisional CTOs, heads of product, executive sponsors, and embedded divisional practitioners to align enterprise standards with business-specific product and engineering requirements. Lead the consolidation of fragmented tooling, resources, licenses, support processes, and automation across both the product and engineering estates, reducing duplication while managing transitions without disrupting delivery. Establish a scalable support and self-service ecosystem for developers and product teams, including developer and product portals, template and artifact libraries, knowledge management, onboarding, access and license management, AI-assisted triage, and expert escalation. Own advocacy and community across both disciplines, including communities of practice, technical and product evangelism, onboarding and enablement content, craft standards for specifications and discovery practice, change communications, and structured feedback loops that earn adoption rather than mandate it. Own the innersource ecosystem, applying open-source working practice to proprietary code so that shared libraries, contribution standards, maintainer stewardship, and IP guardrails make reuse across divisions the default rather than the exception. Define and govern the enterprise approach to AI-native and agentic product development and software engineering, including approved tools, guardrails, model and data access, reusable agent workflows spanning research synthesis, specification drafting, prototype generation, code generation, and release readiness, platform integrations, experimentation, and responsible adoption. Create an enterprise measurement system for product and developer productivity and experience, including DORA metrics, cycle time from idea to release, adoption and utilization measures, tool ROI, practitioner sentiment, friction mapping, product outcome and experimentation results, and executive reporting. Build and lead a high-performing global organization across platform engineering, product management, product operations, design and research enablement, developer support, data and analytics, and forward-deployed AI engineering, with clear accountability and a strong talent strategy. Maintain strong operational rigor, security, resilience, financial management, vendor governance, and continuous improvement across the enterprise toolchain. Compensation/Benefits Information: S&P Global states that the anticipated base salary range for this position is $220,000 to $350,000. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here . What We're Looking For: Basic Required Qualifications: A proven enterprise technology leader who has previously built, transformed, and operated a large-scale Developer Experience, developer platform, DevSecOps, or software engineering enablement function. Minimum of 15 years of progressive technology leadership experience, including responsibility for globally scaled engineering platforms, products, or shared services. Has held enterprise decision rights over tooling used by teams outside their own reporting line, with examples of contested standardization decisions reached alongside divisional CTOs and the trade-offs accepted on risk, cost, and developer experience. Direct ownership of modern product and software development lifecycle platforms in production, including design, source control, CI/CD, building systems, artifact management, developer environments, cloud development infrastructure, application security tooling, and platform integrations. Has owned a platform product roadmap with developers as the customer, including at least one decision to retire or deprioritize a tool that still had an installed user base. Has consolidated overlapping toolchains across multiple business units, and can speak to what was retired, what was recovered in licenses and effort, and how migrations were sequenced without interrupting delivery. Has rolled out AI-assisted development tooling to a developer population at scale, with measured adoption to show for it and defensible answers on guardrails, intellectual property, and model access. Has hired, built, and led a globally distributed organization spanning platform engineering, product management, developer support, and analytics. Excellent executive communication and stakeholder management skills, including the ability to translate technical complexity into clear business decisions, trade-offs, and measurable outcomes. Undergraduate degree required; advanced degree or equivalent relevant experience preferred. Additional Preferred Qualifications: Experience operating developer platforms in a highly regulated, security-conscious, or financial services environment. Experience designing hub-and-spoke operating models that combine enterprise platform ownership with embedded divisional engineering expertise. Has stood up a developer productivity measurement program - DORA metrics, developer sentiment research, adoption and cost data - and used its findings to change a roadmap or investment decision. Experience with enterprise platforms and integrations such as GitHub, Jira, Azure DevOps, Figma, Playwright, CI/CD systems, artifact repositories, developer portals, and API or model context protocol integration layers. Track record of using automation, self-service, data, and AI to improve developer experience and scale support without compromising quality or control. Actively maintains an external view of engineering platform and AI-assisted development practice - through vendor and peer networks, industry forums, or open-source and community participation. . click apply for full job details
11/13/2026
Full time
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 15 The Team: Enterprise Technology & Platforms delivers cross-enterprise technology products, services, and capabilities to S&P Global's organizations and employees worldwide. The Developer Experience and Product Enablement function will own and evolve the enterprise product and software development lifecycle toolchain - the agentic PDLC - bringing together platforms, governance, support, productivity insights, and AI-native product management and engineering capabilities. It spans the full path from discovery and customer insight through definition, design, build, release, and in-market measurement, treating product management and engineering as one connected system rather than two adjacent toolsets. The team will operate as an enterprise hub, partnering closely with divisional CTO and product organizations and embedded practitioners to preserve business context while creating a consistent, scalable experience for both builders and the product leaders who direct them. Responsibilities and Impact: Approximately 10,000 developers across S&P Global build software on a common toolchain, and the product managers, designers, and analysts who decide what gets built work alongside them on a second, largely disconnected one. This role owns both and joins them. That toolchain is critical infrastructure for product discovery, software delivery, engineering productivity, security, resilience, and AI-native development. The role will reduce fragmentation and duplication, close the handoff gaps between product intent and shipped software, strengthen governance and support, and make developer and product experience a measurable strategic capability. Set the enterprise Developer Experience and Product Enablement strategy, product vision, roadmap, operating model, and investment priorities in partnership with the CIO leadership team, divisional CTOs, divisional heads of product, and other senior technology and product leaders. Own the full lifecycle of enterprise software development platforms and tools, including source code management, code collaboration, CI/CD, build engineering, developer environments, code quality and scanning, cloud development infrastructure, and related integrations. Own the full lifecycle of enterprise product management platforms and tools, including customer and market research repositories, idea intake and opportunity assessment, roadmapping and portfolio planning, requirements and specification authoring, design and prototyping, work management and backlog tooling, experimentation and feature management, product analytics, and voice-of-customer and feedback aggregation. Connect the two halves into a single agentic PDLC, establishing the traceable thread from customer insight to opportunity, specification, design, commit, release, and in-market outcome, so that product intent, engineering work, and measured impact reconcile in one system of record rather than in status decks. Manage the toolchain as a coherent portfolio of enterprise products, with clear customer outcomes, service levels, adoption goals, cost transparency, platform health measures, and accountable product ownership. Build a trusted partnership model with divisional CTOs, heads of product, executive sponsors, and embedded divisional practitioners to align enterprise standards with business-specific product and engineering requirements. Lead the consolidation of fragmented tooling, resources, licenses, support processes, and automation across both the product and engineering estates, reducing duplication while managing transitions without disrupting delivery. Establish a scalable support and self-service ecosystem for developers and product teams, including developer and product portals, template and artifact libraries, knowledge management, onboarding, access and license management, AI-assisted triage, and expert escalation. Own advocacy and community across both disciplines, including communities of practice, technical and product evangelism, onboarding and enablement content, craft standards for specifications and discovery practice, change communications, and structured feedback loops that earn adoption rather than mandate it. Own the innersource ecosystem, applying open-source working practice to proprietary code so that shared libraries, contribution standards, maintainer stewardship, and IP guardrails make reuse across divisions the default rather than the exception. Define and govern the enterprise approach to AI-native and agentic product development and software engineering, including approved tools, guardrails, model and data access, reusable agent workflows spanning research synthesis, specification drafting, prototype generation, code generation, and release readiness, platform integrations, experimentation, and responsible adoption. Create an enterprise measurement system for product and developer productivity and experience, including DORA metrics, cycle time from idea to release, adoption and utilization measures, tool ROI, practitioner sentiment, friction mapping, product outcome and experimentation results, and executive reporting. Build and lead a high-performing global organization across platform engineering, product management, product operations, design and research enablement, developer support, data and analytics, and forward-deployed AI engineering, with clear accountability and a strong talent strategy. Maintain strong operational rigor, security, resilience, financial management, vendor governance, and continuous improvement across the enterprise toolchain. Compensation/Benefits Information: S&P Global states that the anticipated base salary range for this position is $220,000 to $350,000. Final base salary for this role will be based on the individual's geographic location, as well as experience level, skill set, training, licenses and certifications. In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan. This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here . What We're Looking For: Basic Required Qualifications: A proven enterprise technology leader who has previously built, transformed, and operated a large-scale Developer Experience, developer platform, DevSecOps, or software engineering enablement function. Minimum of 15 years of progressive technology leadership experience, including responsibility for globally scaled engineering platforms, products, or shared services. Has held enterprise decision rights over tooling used by teams outside their own reporting line, with examples of contested standardization decisions reached alongside divisional CTOs and the trade-offs accepted on risk, cost, and developer experience. Direct ownership of modern product and software development lifecycle platforms in production, including design, source control, CI/CD, building systems, artifact management, developer environments, cloud development infrastructure, application security tooling, and platform integrations. Has owned a platform product roadmap with developers as the customer, including at least one decision to retire or deprioritize a tool that still had an installed user base. Has consolidated overlapping toolchains across multiple business units, and can speak to what was retired, what was recovered in licenses and effort, and how migrations were sequenced without interrupting delivery. Has rolled out AI-assisted development tooling to a developer population at scale, with measured adoption to show for it and defensible answers on guardrails, intellectual property, and model access. Has hired, built, and led a globally distributed organization spanning platform engineering, product management, developer support, and analytics. Excellent executive communication and stakeholder management skills, including the ability to translate technical complexity into clear business decisions, trade-offs, and measurable outcomes. Undergraduate degree required; advanced degree or equivalent relevant experience preferred. Additional Preferred Qualifications: Experience operating developer platforms in a highly regulated, security-conscious, or financial services environment. Experience designing hub-and-spoke operating models that combine enterprise platform ownership with embedded divisional engineering expertise. Has stood up a developer productivity measurement program - DORA metrics, developer sentiment research, adoption and cost data - and used its findings to change a roadmap or investment decision. Experience with enterprise platforms and integrations such as GitHub, Jira, Azure DevOps, Figma, Playwright, CI/CD systems, artifact repositories, developer portals, and API or model context protocol integration layers. Track record of using automation, self-service, data, and AI to improve developer experience and scale support without compromising quality or control. Actively maintains an external view of engineering platform and AI-assisted development practice - through vendor and peer networks, industry forums, or open-source and community participation. . click apply for full job details
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime & Performance Lead Description - As the Principal AI Runtime & Performance Lead, this role is responsible for leading AI runtime architecture, performance optimization, and xPU execution strategy. This role is responsible for the design of end-to-end technology solutions necessary to support the business strategy and objectives. The role develops innovative technology solutions that enable strategic initiatives to scale the business efficiently. The role has strong focus on software development and operational excellence using Agile and lean practices to create market differentiated solutions. Houston office in-office requirement: 4 days Responsibilities • Define runtime architecture. • Lead performance optimization efforts. • Drive benchmark methodology. • Develop model execution strategies. • Plays a critical role in building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Leads the building of standards, designs, and automates the deployment of software. • Drives technology strategy and engineering roadmaps around software engineering. • Assists supervisors with project development, including documentation of features, recording of progress, and creation of the testing plan. • Converts business concepts into the next generation of applications and tools, utilizing adaptive agile methodologies to deliver a minimal viable product to the business. • Assists in scheduling, determining manpower requirements, and estimating costs to project completion in order to meet user requirements. • Contributes innovative ideas and may lead large cross-functional teams, exercising independent judgment to solve unique and complex problems impacting the business. • Acts as a functional manager within area of expertise, developing strategy and setting functional policy and direction. • Provides mentorship and guidance to lower-level employees. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong Linux and Windows expertise. • Experience leading cross-functional engineering teams. Preferred Qualifications • Edge AI platforms. • Device telemetry systems. • Firmware integration experience. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
11/13/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime & Performance Lead Description - As the Principal AI Runtime & Performance Lead, this role is responsible for leading AI runtime architecture, performance optimization, and xPU execution strategy. This role is responsible for the design of end-to-end technology solutions necessary to support the business strategy and objectives. The role develops innovative technology solutions that enable strategic initiatives to scale the business efficiently. The role has strong focus on software development and operational excellence using Agile and lean practices to create market differentiated solutions. Houston office in-office requirement: 4 days Responsibilities • Define runtime architecture. • Lead performance optimization efforts. • Drive benchmark methodology. • Develop model execution strategies. • Plays a critical role in building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Leads the building of standards, designs, and automates the deployment of software. • Drives technology strategy and engineering roadmaps around software engineering. • Assists supervisors with project development, including documentation of features, recording of progress, and creation of the testing plan. • Converts business concepts into the next generation of applications and tools, utilizing adaptive agile methodologies to deliver a minimal viable product to the business. • Assists in scheduling, determining manpower requirements, and estimating costs to project completion in order to meet user requirements. • Contributes innovative ideas and may lead large cross-functional teams, exercising independent judgment to solve unique and complex problems impacting the business. • Acts as a functional manager within area of expertise, developing strategy and setting functional policy and direction. • Provides mentorship and guidance to lower-level employees. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 10+ years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong Linux and Windows expertise. • Experience leading cross-functional engineering teams. Preferred Qualifications • Edge AI platforms. • Device telemetry systems. • Firmware integration experience. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API) • Automation • C++ (Programming Language) • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $147,050 to $230,850 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime / ML Model Systems Engineer Description - This role is responsible for developing runtime abstraction layers and intelligent model placement systems across heterogeneous compute resources In this role, you will ensure the technical design, development, installation, and maintenance of state-of-the-art software applications and services for the company. The role plays a crucial role in building technical solutions to help other developers/engineers deliver faster with modern software and application development tools. Houston in-office requirement: 4 days Responsibilities • Build runtime abstraction frameworks. • Implement model placement policies. • Develop xPU routing logic. • Optimize inference execution. • Leads the building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Builds standards, designs, and automates the deployment of software. • Designs and develops solutions that protect and manage software products and data. • Contributes to technology strategy and engineering roadmaps around software engineering; executes strategic software engineering proof of concepts. • Supervises the work of external engineering vendors, analyzing the testing performed by vendors, and provides feedback and expertise to technicians. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 7-10 years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong AI runtime expertise. • Optimize inference execution. Required Qualifications • ONNX, TensorRT, OpenVINO. • NPU/GPU scheduling. • Edge AI deployment. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API ) • Automation • C++ • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $130,700 to $205,200 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - 25% Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
11/13/2026
Full time
This job is with HP, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. Agentic AI AI Runtime / ML Model Systems Engineer Description - This role is responsible for developing runtime abstraction layers and intelligent model placement systems across heterogeneous compute resources In this role, you will ensure the technical design, development, installation, and maintenance of state-of-the-art software applications and services for the company. The role plays a crucial role in building technical solutions to help other developers/engineers deliver faster with modern software and application development tools. Houston in-office requirement: 4 days Responsibilities • Build runtime abstraction frameworks. • Implement model placement policies. • Develop xPU routing logic. • Optimize inference execution. • Leads the building of various software development projects and platforms while aligning them with business and security strategies and requirements. • Builds standards, designs, and automates the deployment of software. • Designs and develops solutions that protect and manage software products and data. • Contributes to technology strategy and engineering roadmaps around software engineering; executes strategic software engineering proof of concepts. • Supervises the work of external engineering vendors, analyzing the testing performed by vendors, and provides feedback and expertise to technicians. Education & Experience Recommended • Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence. • Typically has 7-10 years of work experience, preferably in software designing & development, software architecture, programming languages, or a related field. • Strong AI runtime expertise. • Optimize inference execution. Required Qualifications • ONNX, TensorRT, OpenVINO. • NPU/GPU scheduling. • Edge AI deployment. Knowledge & Skills • Agile Methodology • Amazon Web Services • Application Programming Interface (API ) • Automation • C++ • Computer Science • DevOps • Docker (Software) • Full Stack Development • Java (Programming Language) • JavaScript (Programming Language) • Kubernetes • Microservices • Microsoft Azure • Python (Programming Language) • React.js • Scalability • Software Development • Software Engineering • SQL (Programming Language) The pay range for this role is $130,700 to $205,200 USD annually with additional opportunities for pay in the form of bonus and/or equity (applies to United States of America candidates only). Pay varies by work location, job-related knowledge, skills, and experience. Benefits: HP offers a comprehensive benefits package for this position, including: Health insurance Dental insurance Vision insurance Long term/short term disability insurance Employee assistance program Flexible spending account Life insurance Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure 11 paid holidays Additional flexible paid vacation and sick leave ( US benefits overview ) The compensation and benefits information is accurate as of the date of this posting. The Company reserves the right to modify this information at any time, with or without notice, subject to applicable law. Job - Software Schedule - Full time Shift - No shift premium (United States of America) Travel - 25% Relocation - Equal Opportunity Employer (EEO) - HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s). Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence. For more information, review HP's EEO Policy or read about your rights as an applicant under the law here: " Know Your Rights: Workplace Discrimination is Illegal "
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 13 Role Summary We are seeking a Technical Team Lead - AI, AWS, Java Full-Stack, Financial Platforms to lead the design, development, and delivery of index calculation and back testing platform. This role combines hands-on Java full-stack engineering, AWS cloud development, AI-assisted software delivery, and technical leadership across a financial technology platform. The Technical Team Lead will guide a team of engineers in building scalable backend services, modern user interfaces, financial calculation workflows, back testing capabilities, data integrations, automated testing frameworks, and AI-assisted QA/evaluation routines. The role requires strong technical judgment, practical leadership, and the ability to translate financial methodology requirements into reliable, auditable, and production-ready software. This is a hands-on leadership role. The successful candidate will be expected to define technical direction, mentor developers, review architecture and code, collaborate with business and quantitative stakeholders, and contribute directly to critical platform components. Key Responsibilities Technical Leadership Lead the engineering delivery of an AI-enabled financial platform for index calculation, options analytics, back testing, and workflow execution. Define technical architecture, implementation standards, coding practices, testing expectations, and delivery patterns for the engineering team. Guide developers through complex design decisions involving Java services, frontend architecture, AWS workflows, data integration, AI-assisted development, and calculation accuracy. Partner with product owners, quantitative analysts, QA teams, infrastructure teams, data teams, and business stakeholders to convert requirements into clear technical plans. Lead design reviews, code reviews, sprint technical planning, production readiness reviews, and technical risk assessments. Mentor engineers in Java full-stack development, cloud-native design, financial calculation systems, automated testing, and responsible use of AI-assisted engineering tools. Ensure the platform is scalable, secure, maintainable, observable, auditable, and aligned with financial methodology and operational requirements. Hands-On Java Full-Stack Development Design and develop backend services using Java, Spring Boot, REST APIs, and enterprise application patterns. Build platform components for index calculation, backtesting, data processing, workflow orchestration, exception handling, validation, and reporting. Implement financial calculation logic based on methodology specifications, including options-based strategies, rebalancing rules, pricing inputs, market calendars, and historical backtesting assumptions. Develop modern frontend applications using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Build user interfaces for index setup, backtest configuration, workflow monitoring, calculation review, validation results, exception management, dashboards, and reporting. Ensure strong integration between frontend applications, backend APIs, authentication flows, data services, and cloud workflows. AI-Assisted Engineering and Spec-Driven Development Apply Spec-Driven Development practices to convert financial methodology documents, business requirements, and technical specifications into testable software components. Use AI-assisted engineering workflows to support planning, code generation, refactoring, test creation, documentation, and quality review. Review AI-generated or AI-assisted code for correctness, maintainability, security, performance, test coverage, and alignment with platform standards. Help establish team practices for responsible AI-assisted development, including review checklists, validation gates, test coverage expectations, and documentation standards. Support AI-assisted QA and evaluation routines for generated code, calculation outputs, regression testing, and backtest validation. AWS, Data, and Platform Engineering Design and implement AWS-based platform components using services such as AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, and AWS RDS. Build workflow orchestration for index calculations, backtest execution, data validation, exception handling, approvals, and operational monitoring. Integrate with data platforms including AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), data lakes, market data sources, reference data platforms, and analytical data pipelines. Ensure data lineage, audit trails, input/output traceability, logging, alerting, and operational controls are built into the platform. Support CI/CD, infrastructure automation, deployment validation, monitoring, and production support practices. Required Experience 12+ years of software engineering experience, with significant experience in Java full-stack development and enterprise platform delivery. 5+ years of technical leadership experience, including mentoring engineers, leading design discussions, reviewing code, and guiding delivery teams. Strong hands-on experience with Java, Spring Boot, REST APIs, microservices, relational databases, and backend service design. Hands-on frontend development experience using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Experience designing and delivering large-scale systems involving distributed services, workflow orchestration, data processing, APIs, and production operations. Experience with AWS cloud-native development, including compute, storage, orchestration, security, monitoring, logging, and managed databases. Strong understanding of automated testing, CI/CD, code quality, observability, secure development, and production readiness. Experience or strong interest in financial platforms, especially index calculation, options analytics, derivatives, equities, portfolio analytics, backtesting, risk systems, or capital markets technology. Ability to interpret detailed financial methodology specifications and translate them into reliable, testable, and auditable software designs. Exposure to GenAI engineering, AI-assisted coding, agentic development workflows, Claude Code, Claude Code CLI, Spec Kit, or Spec-Driven Development is highly desirable. Preferred Technical Stack Backend: Java, Spring Boot, REST APIs, microservices, JPA/Hibernate, Maven/Gradle, concurrency, batch processing, and enterprise integration patterns. Frontend: React, Angular, or Vue; TypeScript; JavaScript; HTML; CSS; reusable components; dashboards; forms; data grids; charts; and responsive UI design. Cloud: AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, RDS, and cloud-native security patterns. Data Platforms: AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), relational databases, data pipelines, market data integration, reference data, and analytical data processing. AI Engineering: AI-assisted development, Spec-Driven Development, Claude Code, Claude Code CLI, Spec Kit, automated QA/evaluation routines, and human-reviewed generated code. DevOps and Quality: CI/CD, automated testing, integration testing, regression testing, performance testing, logging, monitoring, alerting, and production support. Financial Domain Knowledge The ideal candidate should have experience or strong working interest in financial systems involving calculation-heavy workflows. Relevant areas include: Index calculation methodologies, index levels, divisor logic, rebalancing, weighting, corporate actions, calendars, and daily calculation cycles. Options-based strategies such as covered call, put write, collar, volatility-based, delta-based, or rules-based options strategies. Backtesting concepts such as historical simulation, look-ahead bias prevention, survivorship bias, transaction assumptions, rebalance simulation, and reproducibility. Market data concepts including prices, option chains, strikes, expiries, implied volatility, rates, dividends, corporate actions, and reference data. Validation practices including golden datasets, tolerance checks, independent calculation verification, reconciliation, audit trails, and exception handling. Success Measures Leads the team in delivering a scalable, secure, and reliable index calculation and backtesting platform. Produces and guides high-quality Java full-stack implementation across backend services, frontend applications, APIs, workflows, and data integrations. Converts financial methodology specifications into tested, reproducible, and auditable platform logic. Establishes strong engineering practices for code quality, automated testing, observability, documentation, and production readiness. Uses AI-assisted development responsibly to improve delivery speed while maintaining human review, financial accuracy, and software quality. Builds strong collaboration across engineering, quantitative analysis, QA, infrastructure, product . click apply for full job details
11/13/2026
Full time
This job is with S&P Global, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. About the Role: Grade Level (for internal use): 13 Role Summary We are seeking a Technical Team Lead - AI, AWS, Java Full-Stack, Financial Platforms to lead the design, development, and delivery of index calculation and back testing platform. This role combines hands-on Java full-stack engineering, AWS cloud development, AI-assisted software delivery, and technical leadership across a financial technology platform. The Technical Team Lead will guide a team of engineers in building scalable backend services, modern user interfaces, financial calculation workflows, back testing capabilities, data integrations, automated testing frameworks, and AI-assisted QA/evaluation routines. The role requires strong technical judgment, practical leadership, and the ability to translate financial methodology requirements into reliable, auditable, and production-ready software. This is a hands-on leadership role. The successful candidate will be expected to define technical direction, mentor developers, review architecture and code, collaborate with business and quantitative stakeholders, and contribute directly to critical platform components. Key Responsibilities Technical Leadership Lead the engineering delivery of an AI-enabled financial platform for index calculation, options analytics, back testing, and workflow execution. Define technical architecture, implementation standards, coding practices, testing expectations, and delivery patterns for the engineering team. Guide developers through complex design decisions involving Java services, frontend architecture, AWS workflows, data integration, AI-assisted development, and calculation accuracy. Partner with product owners, quantitative analysts, QA teams, infrastructure teams, data teams, and business stakeholders to convert requirements into clear technical plans. Lead design reviews, code reviews, sprint technical planning, production readiness reviews, and technical risk assessments. Mentor engineers in Java full-stack development, cloud-native design, financial calculation systems, automated testing, and responsible use of AI-assisted engineering tools. Ensure the platform is scalable, secure, maintainable, observable, auditable, and aligned with financial methodology and operational requirements. Hands-On Java Full-Stack Development Design and develop backend services using Java, Spring Boot, REST APIs, and enterprise application patterns. Build platform components for index calculation, backtesting, data processing, workflow orchestration, exception handling, validation, and reporting. Implement financial calculation logic based on methodology specifications, including options-based strategies, rebalancing rules, pricing inputs, market calendars, and historical backtesting assumptions. Develop modern frontend applications using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Build user interfaces for index setup, backtest configuration, workflow monitoring, calculation review, validation results, exception management, dashboards, and reporting. Ensure strong integration between frontend applications, backend APIs, authentication flows, data services, and cloud workflows. AI-Assisted Engineering and Spec-Driven Development Apply Spec-Driven Development practices to convert financial methodology documents, business requirements, and technical specifications into testable software components. Use AI-assisted engineering workflows to support planning, code generation, refactoring, test creation, documentation, and quality review. Review AI-generated or AI-assisted code for correctness, maintainability, security, performance, test coverage, and alignment with platform standards. Help establish team practices for responsible AI-assisted development, including review checklists, validation gates, test coverage expectations, and documentation standards. Support AI-assisted QA and evaluation routines for generated code, calculation outputs, regression testing, and backtest validation. AWS, Data, and Platform Engineering Design and implement AWS-based platform components using services such as AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, and AWS RDS. Build workflow orchestration for index calculations, backtest execution, data validation, exception handling, approvals, and operational monitoring. Integrate with data platforms including AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), data lakes, market data sources, reference data platforms, and analytical data pipelines. Ensure data lineage, audit trails, input/output traceability, logging, alerting, and operational controls are built into the platform. Support CI/CD, infrastructure automation, deployment validation, monitoring, and production support practices. Required Experience 12+ years of software engineering experience, with significant experience in Java full-stack development and enterprise platform delivery. 5+ years of technical leadership experience, including mentoring engineers, leading design discussions, reviewing code, and guiding delivery teams. Strong hands-on experience with Java, Spring Boot, REST APIs, microservices, relational databases, and backend service design. Hands-on frontend development experience using React, Angular, Vue, TypeScript, JavaScript, HTML, and CSS. Experience designing and delivering large-scale systems involving distributed services, workflow orchestration, data processing, APIs, and production operations. Experience with AWS cloud-native development, including compute, storage, orchestration, security, monitoring, logging, and managed databases. Strong understanding of automated testing, CI/CD, code quality, observability, secure development, and production readiness. Experience or strong interest in financial platforms, especially index calculation, options analytics, derivatives, equities, portfolio analytics, backtesting, risk systems, or capital markets technology. Ability to interpret detailed financial methodology specifications and translate them into reliable, testable, and auditable software designs. Exposure to GenAI engineering, AI-assisted coding, agentic development workflows, Claude Code, Claude Code CLI, Spec Kit, or Spec-Driven Development is highly desirable. Preferred Technical Stack Backend: Java, Spring Boot, REST APIs, microservices, JPA/Hibernate, Maven/Gradle, concurrency, batch processing, and enterprise integration patterns. Frontend: React, Angular, or Vue; TypeScript; JavaScript; HTML; CSS; reusable components; dashboards; forms; data grids; charts; and responsive UI design. Cloud: AWS Step Functions, Lambda, ECS/EKS, API Gateway, S3, CloudWatch, IAM, EventBridge, SQS/SNS, RDS, and cloud-native security patterns. Data Platforms: AWS RDS, cloud data platforms (such as Databricks, Snowflake, or Azure Synapse), relational databases, data pipelines, market data integration, reference data, and analytical data processing. AI Engineering: AI-assisted development, Spec-Driven Development, Claude Code, Claude Code CLI, Spec Kit, automated QA/evaluation routines, and human-reviewed generated code. DevOps and Quality: CI/CD, automated testing, integration testing, regression testing, performance testing, logging, monitoring, alerting, and production support. Financial Domain Knowledge The ideal candidate should have experience or strong working interest in financial systems involving calculation-heavy workflows. Relevant areas include: Index calculation methodologies, index levels, divisor logic, rebalancing, weighting, corporate actions, calendars, and daily calculation cycles. Options-based strategies such as covered call, put write, collar, volatility-based, delta-based, or rules-based options strategies. Backtesting concepts such as historical simulation, look-ahead bias prevention, survivorship bias, transaction assumptions, rebalance simulation, and reproducibility. Market data concepts including prices, option chains, strikes, expiries, implied volatility, rates, dividends, corporate actions, and reference data. Validation practices including golden datasets, tolerance checks, independent calculation verification, reconciliation, audit trails, and exception handling. Success Measures Leads the team in delivering a scalable, secure, and reliable index calculation and backtesting platform. Produces and guides high-quality Java full-stack implementation across backend services, frontend applications, APIs, workflows, and data integrations. Converts financial methodology specifications into tested, reproducible, and auditable platform logic. Establishes strong engineering practices for code quality, automated testing, observability, documentation, and production readiness. Uses AI-assisted development responsibly to improve delivery speed while maintaining human review, financial accuracy, and software quality. Builds strong collaboration across engineering, quantitative analysis, QA, infrastructure, product . click apply for full job details
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field +2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning). +2 years experience leveraging Agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang +2 years Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 5, Senior Manager - Intelligent Foundations and Experiences (IFX) Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field +2 years experience building production RAG pipelines (chunking, embeddings, vector indexing, graph RAG, or fine-tuning). +2 years experience leveraging Agentic patterns (Tool Calling, ReAct loops, Plan-and-Execute, Multi-Agent Collaboration). +2 years with LLM orchestration frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel) and model APIs (OpenAI, Anthropic, Bedrock, Ollama, Hugging Face). +2 year experience in building agentic AI systems and agentic workflows +2 year experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang +2 years Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Manager IC Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. As part of the Enterprise ML Platform team, you will build and evolve the high-throughput, multi-tenant training platform that powers model workflows across Capital One-ranging from classical ML to GenAI fine-tuning and distributed computing with Ray, Spark, and Dask. Owning the Kubeflow Pipelines v2 application layer on Amazon EKS, the team develops internal Python and Go SDKs, custom Kubernetes operators, and developer tooling that abstract complex infrastructure for critical, regulated workloads. In this role, you will integrate agentic AI into modern engineering lifecycles and contribute directly to upstream open-source Kubeflow, balancing fast-paced feature delivery with enterprise-grade platform stability and security. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years designing, training, optimizing, and evaluating modern ML models across architectures (e.g., Transformers, CNNs, RNNs) and paradigms (supervised, unsupervised, reinforcement learning), including loss design, hyperparameter tuning, and diagnostic debugging. 3+ years architecting and scaling distributed, end-to-end ML systems, from production-ready training/evaluation data pipelines to algorithm and infrastructure optimization. 3+ years managing ML workloads using Docker, Kubernetes, and pipeline orchestration tools (e.g., Kubeflow is a strong plus). 3+ years applying modern software best practices (CI/CD, version control, automated testing, code reviews) and deploying resilient systems with progressive rollout strategies (blue/green, canary/one-box), monitoring, alerting, and incident response planning. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 4 - Manager IC Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. As part of the Enterprise ML Platform team, you will build and evolve the high-throughput, multi-tenant training platform that powers model workflows across Capital One-ranging from classical ML to GenAI fine-tuning and distributed computing with Ray, Spark, and Dask. Owning the Kubeflow Pipelines v2 application layer on Amazon EKS, the team develops internal Python and Go SDKs, custom Kubernetes operators, and developer tooling that abstract complex infrastructure for critical, regulated workloads. In this role, you will integrate agentic AI into modern engineering lifecycles and contribute directly to upstream open-source Kubeflow, balancing fast-paced feature delivery with enterprise-grade platform stability and security. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years designing, training, optimizing, and evaluating modern ML models across architectures (e.g., Transformers, CNNs, RNNs) and paradigms (supervised, unsupervised, reinforcement learning), including loss design, hyperparameter tuning, and diagnostic debugging. 3+ years architecting and scaling distributed, end-to-end ML systems, from production-ready training/evaluation data pipelines to algorithm and infrastructure optimization. 3+ years managing ML workloads using Docker, Kubernetes, and pipeline orchestration tools (e.g., Kubeflow is a strong plus). 3+ years applying modern software best practices (CI/CD, version control, automated testing, code reviews) and deploying resilient systems with progressive rollout strategies (blue/green, canary/one-box), monitoring, alerting, and incident response planning. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Machine Learning Engineer 4 - Manager IC Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. As part of the Enterprise ML Platform team, you will build and evolve the high-throughput, multi-tenant training platform that powers model workflows across Capital One-ranging from classical ML to GenAI fine-tuning and distributed computing with Ray, Spark, and Dask. Owning the Kubeflow Pipelines v2 application layer on Amazon EKS, the team develops internal Python and Go SDKs, custom Kubernetes operators, and developer tooling that abstract complex infrastructure for critical, regulated workloads. In this role, you will integrate agentic AI into modern engineering lifecycles and contribute directly to upstream open-source Kubeflow, balancing fast-paced feature delivery with enterprise-grade platform stability and security. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years designing, training, optimizing, and evaluating modern ML models across architectures (e.g., Transformers, CNNs, RNNs) and paradigms (supervised, unsupervised, reinforcement learning), including loss design, hyperparameter tuning, and diagnostic debugging. 3+ years architecting and scaling distributed, end-to-end ML systems, from production-ready training/evaluation data pipelines to algorithm and infrastructure optimization. 3+ years managing ML workloads using Docker, Kubernetes, and pipeline orchestration tools (e.g., Kubeflow is a strong plus). 3+ years applying modern software best practices (CI/CD, version control, automated testing, code reviews) and deploying resilient systems with progressive rollout strategies (blue/green, canary/one-box), monitoring, alerting, and incident response planning. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
11/13/2026
Full time
Machine Learning Engineer 4 - Manager IC Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you'll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. As part of the Enterprise ML Platform team, you will build and evolve the high-throughput, multi-tenant training platform that powers model workflows across Capital One-ranging from classical ML to GenAI fine-tuning and distributed computing with Ray, Spark, and Dask. Owning the Kubeflow Pipelines v2 application layer on Amazon EKS, the team develops internal Python and Go SDKs, custom Kubernetes operators, and developer tooling that abstract complex infrastructure for critical, regulated workloads. In this role, you will integrate agentic AI into modern engineering lifecycles and contribute directly to upstream open-source Kubeflow, balancing fast-paced feature delivery with enterprise-grade platform stability and security. What You'll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 4 years of experience programming with Python, Java, Golang, or C++ At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data At least 2 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized Machine Learning software systems Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years designing, training, optimizing, and evaluating modern ML models across architectures (e.g., Transformers, CNNs, RNNs) and paradigms (supervised, unsupervised, reinforcement learning), including loss design, hyperparameter tuning, and diagnostic debugging. 3+ years architecting and scaling distributed, end-to-end ML systems, from production-ready training/evaluation data pipelines to algorithm and infrastructure optimization. 3+ years managing ML workloads using Docker, Kubernetes, and pipeline orchestration tools (e.g., Kubeflow is a strong plus). 3+ years applying modern software best practices (CI/CD, version control, automated testing, code reviews) and deploying resilient systems with progressive rollout strategies (blue/green, canary/one-box), monitoring, alerting, and incident response planning. 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation Authored/co-authored a paper on a ML technique, model, or proof of concept At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer ). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4 New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4 San Jose, CA: $215,200 - $245,600 for Machine Learning Engineer 4 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job Description Job Description Genesis10 is currently seeking a Senior AI Engineer for a contract to hire position with a Regional Financial Institution located in Columbus, OH. This is a 3+ month contract-to-hire opportunity. Candidates can also be located in: Charlotte, NC; Atlanta, GA: Chicago, IL; Minnetonka, MN; Detroit, MI; Dallas, TX. Compensation: $65.00 - $75.00 per hour, W2, based on qualifications Position Overview: We are looking for a talented Senior AI Engineer to contribute to the design, development, and support of AI tools and platforms for developers across the company. This is a hands-on engineering role centered on GCP, Gemini, Vertex AI, Java Spring Boot, and React.js. The ideal candidate will have demonstrable experience building and integrating with AI tools and services to deliver reliable, secure, and maintainable solutions that accelerate software development. Key Responsibilities: Develop and maintain AI platforms, tools, and frameworks used by engineers across the company, including Claude Code, GitHub Copilot, MCP servers, plugins, skills, and agentic frameworks Implement AI platform services, orchestration patterns, reference implementations, and shared integration components Design and deliver tools that support the development of custom agents and workflows Integrate and operationalize AI tools and services with cloud, security, development, and enterprise technology platforms Build secure, scalable, reliable, observable, performant, and maintainable services for custom agents and AI tool integrations Provide technical support and guidance to development teams building, deploying, and operating custom agents and MCP servers Contribute to framework lifecycle practices, including versioning, release management, documentation, adoption, support, and continuous improvement Implement logging, metrics, token-utilization monitoring, tracing, and other operational capabilities for AI services running on GCP Apply enterprise security, privacy, responsible AI, access-control, governance, cost-management, and model-risk practices to AI solutions Collaborate with development teams, security, and architecture to define requirements and deliver platform capabilities Participate in code reviews, technical discussions, troubleshooting, and knowledge-sharing activities Mentor junior engineers on the team and on development teams, contributing to a culture of continuous improvement Primary Requirements: Bachelor's degree or equivalent work experience in computer science, engineering, artificial intelligence, or a related field 5-7+ years of experience in software engineering, platform engineering, AI engineering, or a related technical discipline Proven experience delivering high-quality software solutions in production environments Hands-on experience building or integrating AI, LLM, developer-platform, or automation capabilities Experience with cloud-based AI services platforms such as GCP/AWS Gemini, and Vertex AI or comparable model platforms Solid understanding of application architecture, integration patterns, APIs, and software design principles Experience developing Java REST APIs and services with Spring Boot and working knowledge of React.js or comparable front-end technologies Experience with secure API integrations and OAuth 2.0 / OpenID Connect authorization patterns Understanding of the software development lifecycle, CI/CD, observability, reliability, security, privacy, and responsible AI practices Strong problem-solving skills, attention to detail, technical communication, and ability to collaborate effectively across teams AI Platforms: GCP/AWS Cloud, Gemini, Vertex AI, model garden, model runtime, model gateway, and agent gateway AI Engineering: custom agent design, sequential workflows, multi-agent systems, deterministic graph-based agents, and reusable orchestration patterns Developer Tools: Claude Code, GitHub Copilot, custom instructions, prompts, skills, plugins, and extensions Agent Integration: MCP servers and clients, tools, resources, data-source integrations, A2A patterns, and agent-to-agent communication Frameworks: Google ADK, Spring AI, LangChain, LangChain4j, or comparable AI/LLM integration libraries Application Development: Java, Spring Boot, REST APIs, React.js, microservices, and cloud-native application patterns Security and Governance: OAuth 2.0, OpenID Connect, service accounts, delegated access, model governance, GCP Model Armor, privacy, responsible AI, and access control Operations: CI/CD, Harness, Azure DevOps, logging, metrics, tracing, token utilization, performance, reliability, and incident support Desired Skills: Hands-on experience using Claude Code and GitHub Copilot in an engineering workflow Designing or implementing custom AI agents, reusable orchestration patterns, shared integrations, or reference implementations Building sequential, multi-agent, or deterministic graph-based agent workflows Building or integrating MCP servers and clients to expose tools, resources, or data sources to AI agents Enabling agent-to-agent communication using A2A or comparable protocols Experience with Google ADK, Spring AI, LangChain, LangChain4j, or similar LLM integration libraries and SDKs Experience with Gemini Agent Platform / Vertex AI capabilities such as model garden, model runtime, model gateway, or agent gateway Implementing model governance controls such as GCP Model Armor, cost controls, token limits, rate limits, and access policies Implementing logging, metrics, distributed tracing, token-utilization monitoring, and operational dashboards for AI services on GCP Exposure to containerization, microservices, and cloud-native application architecture Experience working with CI/CD pipelines in Harness and Azure DevOps Familiarity with Agile/Scrum methodologies and development practices for shared platform capabilities 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 of 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 for a contract to hire position with a Regional Financial Institution located in Columbus, OH. This is a 3+ month contract-to-hire opportunity. Candidates can also be located in: Charlotte, NC; Atlanta, GA: Chicago, IL; Minnetonka, MN; Detroit, MI; Dallas, TX. Compensation: $65.00 - $75.00 per hour, W2, based on qualifications Position Overview: We are looking for a talented Senior AI Engineer to contribute to the design, development, and support of AI tools and platforms for developers across the company. This is a hands-on engineering role centered on GCP, Gemini, Vertex AI, Java Spring Boot, and React.js. The ideal candidate will have demonstrable experience building and integrating with AI tools and services to deliver reliable, secure, and maintainable solutions that accelerate software development. Key Responsibilities: Develop and maintain AI platforms, tools, and frameworks used by engineers across the company, including Claude Code, GitHub Copilot, MCP servers, plugins, skills, and agentic frameworks Implement AI platform services, orchestration patterns, reference implementations, and shared integration components Design and deliver tools that support the development of custom agents and workflows Integrate and operationalize AI tools and services with cloud, security, development, and enterprise technology platforms Build secure, scalable, reliable, observable, performant, and maintainable services for custom agents and AI tool integrations Provide technical support and guidance to development teams building, deploying, and operating custom agents and MCP servers Contribute to framework lifecycle practices, including versioning, release management, documentation, adoption, support, and continuous improvement Implement logging, metrics, token-utilization monitoring, tracing, and other operational capabilities for AI services running on GCP Apply enterprise security, privacy, responsible AI, access-control, governance, cost-management, and model-risk practices to AI solutions Collaborate with development teams, security, and architecture to define requirements and deliver platform capabilities Participate in code reviews, technical discussions, troubleshooting, and knowledge-sharing activities Mentor junior engineers on the team and on development teams, contributing to a culture of continuous improvement Primary Requirements: Bachelor's degree or equivalent work experience in computer science, engineering, artificial intelligence, or a related field 5-7+ years of experience in software engineering, platform engineering, AI engineering, or a related technical discipline Proven experience delivering high-quality software solutions in production environments Hands-on experience building or integrating AI, LLM, developer-platform, or automation capabilities Experience with cloud-based AI services platforms such as GCP/AWS Gemini, and Vertex AI or comparable model platforms Solid understanding of application architecture, integration patterns, APIs, and software design principles Experience developing Java REST APIs and services with Spring Boot and working knowledge of React.js or comparable front-end technologies Experience with secure API integrations and OAuth 2.0 / OpenID Connect authorization patterns Understanding of the software development lifecycle, CI/CD, observability, reliability, security, privacy, and responsible AI practices Strong problem-solving skills, attention to detail, technical communication, and ability to collaborate effectively across teams AI Platforms: GCP/AWS Cloud, Gemini, Vertex AI, model garden, model runtime, model gateway, and agent gateway AI Engineering: custom agent design, sequential workflows, multi-agent systems, deterministic graph-based agents, and reusable orchestration patterns Developer Tools: Claude Code, GitHub Copilot, custom instructions, prompts, skills, plugins, and extensions Agent Integration: MCP servers and clients, tools, resources, data-source integrations, A2A patterns, and agent-to-agent communication Frameworks: Google ADK, Spring AI, LangChain, LangChain4j, or comparable AI/LLM integration libraries Application Development: Java, Spring Boot, REST APIs, React.js, microservices, and cloud-native application patterns Security and Governance: OAuth 2.0, OpenID Connect, service accounts, delegated access, model governance, GCP Model Armor, privacy, responsible AI, and access control Operations: CI/CD, Harness, Azure DevOps, logging, metrics, tracing, token utilization, performance, reliability, and incident support Desired Skills: Hands-on experience using Claude Code and GitHub Copilot in an engineering workflow Designing or implementing custom AI agents, reusable orchestration patterns, shared integrations, or reference implementations Building sequential, multi-agent, or deterministic graph-based agent workflows Building or integrating MCP servers and clients to expose tools, resources, or data sources to AI agents Enabling agent-to-agent communication using A2A or comparable protocols Experience with Google ADK, Spring AI, LangChain, LangChain4j, or similar LLM integration libraries and SDKs Experience with Gemini Agent Platform / Vertex AI capabilities such as model garden, model runtime, model gateway, or agent gateway Implementing model governance controls such as GCP Model Armor, cost controls, token limits, rate limits, and access policies Implementing logging, metrics, distributed tracing, token-utilization monitoring, and operational dashboards for AI services on GCP Exposure to containerization, microservices, and cloud-native application architecture Experience working with CI/CD pipelines in Harness and Azure DevOps Familiarity with Agile/Scrum methodologies and development practices for shared platform capabilities 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 of 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.
Locations: Atlanta Austin Boston Brooklyn Chicago Dallas Denver Detroit Houston Miami Minneapolis Nashville New York Philadelphia Pittsburgh Durham Summit Washington Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. BCG's Tech and Digital Advantage (TDA) practice focuses on helping clients deliver competitive advantage and business superior performance through data, technology and digital. BCG Platinion sits within the TDA practice and is at the heart of the strategic impact we have with our clients. Our consultants and experts globally work across all industries and provide deep experience and expertise in a wide variety of topics including Tech Advisory and Delivery, Architecture, Enterprise Solutions and Packaged Software, Cybersecurity, and Technology Risk Management. Our Tech Advisory and Delivery Chapter within BCG Platinion helps clients solve some of their most challenging problems through the development of superior IT concepts and tech solutions. The ideal candidate is both passionate as a consultant and technologist, and can bring their expertise to help develop customized, innovative client solutions. Tech Advisory & Delivery Managers at BCG Platinion are: Technical experts. They are critical thinkers and have extensive IT expertise that drives innovation for our clients, rooted in practicality. Data-driven storytellers. They gather information, evaluate against their expertise and build clear, insightful paths for clients. Collaborative. They are interdisciplinary team players who seek alignment and establish relationships ranging from cross-functional stakeholder groups to existing teams. Comfortable with ambiguity. They know the path forward isn't always well-defined. They are comfortable and confident working through the unknown. Change agents. They know how to make change happen across an organization across all levels - from executives to individual contributors and IT practitioners. They can align and onboard teams to implement new processes and toolsets. They embrace complex challenges and guide an organization to optimize IT best practices. Influencers. They build strong relationships to build trust and influence stakeholders. They are able to effectively communicate across Business & IT stakeholders in order to influence positive change. AI and Agentic native. They are versed in the latest AI and Agentic technologies and methodologies and leverage them daily to deliver high impact outcomes and tackle difficult challenges. About BCG Platinion BCG Platinion's presence spans across the globe, with offices in Asia, Europe, and South and North America. We achieve digital excellence for clients with sustained solutions to the most complex and time-sensitive challenge. We guide clients into the future to push the status quo, overcome tech limitations, and enable our clients to go further in their digital journeys than what has ever been possible in the past. At BCG Platinion, we deliver business value through the innovative use of technology at a rapid pace. We roll up our sleeves to transform business, revolutionize approaches, satisfy customers, and change the game through Architecture, Cybersecurity, Digital Transformation, Enterprise Application and Risk functions. We balance vision with a pragmatic path to change transforming strategies into leading-edge tech platforms, at scale. What You'll Do As a manager, you'll be given end-to-end responsibility for the larger and more complex "modules" within a BCG project and begin to develop specialized knowledge to help you solve our clients' problems. You'll work on a variety of digital topics, applying generalist consulting skills to strategic digital & technology questions. Working together with clients to understand their issues, you'll create strategies for change, win buy-in for your recommendations, and collaborate with fellow BCGers to transform client potential into performance. Given your role in leading larger and more complex "modules", you will manage, support, and coach more junior team members in addition to also serving as an individual contributor yourself. Our consultants within the Tech & Digital Advantage (TDA) Chapter are an integral part of BCG's core consulting team; we work side-by-side with all practice areas to create value and competitive advantage for our clients. You'll help your clients answer questions such as "How will AI disrupt my business model?", "How can businesses use data and analytics to create highly personalized outreach delivered through a seamless omnichannel experience?", "How can I ship higher quality digital services to my customers faster by using agile?" and many more. You're Good At: At Platinion, we expect our consultants to be able to contribute and quickly get up to speed on a variety of topics to support the ever-changing demands of our clients. However, that broad ability to deliver needs to be grounded in deep technological knowledge in 2-3 of our primary areas of expertise such as; Expertise Supporting AI and digital transformation efforts by developing strategies around: AI and Agentic Platforms. Data and digital analytics platforms. Cloud infrastructure and technologies. Data management capabilities. Enterprise Tech Platforms. Business IT architecture. Software and product management (including Agile ways of working). Tech, Enterprise Architecture and Data governance. Experience with a wide breadth of tech / AI / digital offerings, including but not limited to: Developing roadmaps and current state assessments for IT and AI/Data organizations in large companies across various industries. Orchestrating technical program delivery across business stakeholders, complex vendor landscapes and technology ecosystems. AI / LLM cost optimization and FinOps. IT Benchmarking and recommendations for IT cost take-out initiatives. Developing future state tech vendor landscape, vendor assessments/selections automation, tech cost benefits analysis, eCommerce, platform valuation and design. Supporting tech functions during mergers and acquisitions, including the functional and technical transformation of an organization's IT department. Communicating the differences and benefits between multiple cloud computer providers and strategies for migrating from on-premise architecture. Utilizing working knowledge and experience with GenAI and its potential use cases and client implications to deliver both practical and visionary solutions. Experience leading the design and delivery of AI-powered products within a functional and/or industry business domain, including: Defining AI product vision, roadmaps, and prioritization frameworks grounded in domain-specific workflows and business value. Translating business strategy into AI-enabled product concepts, functional specifications, and delivery plans. Leading agile product delivery including sprint planning, backlog management, and iterative development across teams. Owning product quality assurance and ensuring outputs meet functional, technical, and compliance requirements as well as catch bad AI engineering. Defining product / solution architecture and data integration patterns. Designing and overseeing the integration of AI and generative AI capabilities into enterprise workflows at scale. Defining data strategy and governance requirements to underpin reliable, production-grade AI products. Leading the design of agentic workflows and automation use cases, balancing innovation with operational feasibility. Leading vendor evaluations and platform selection processes for AI product tooling, aligned to business and technical requirements. Driving change management and adoption strategies to embed AI products into business operations and ways of working. Optimizing business and IT processes within complex and heavily matrixed organizations and effectively communicating a path forward for clients and internal stakeholders. Delivering data and digital platforms using techniques such as Agile, DevSecOps, and Cloud native architectures. Specific AI product domain expertise topics (preferred): FP&A & FinOps: Lead the design and delivery of AI-powered products and subject matter depth in one or multiple core finance processes, including FP&A, financial close and reporting, procure to pay, order to cash, etc., with understanding of underlying finance systems (e.g. ERP, CLM, EPM, etc.) and data (e.g., GL, Orders, Invoices, Contracts, Plan/Forecast, etc.). Experience deploying AI use cases ranging from operational quick wins (e.g., AI chat enabled reporting insights) to strategic transformation (e.g., AI order-to-cash automation). Supply Chain / S&OP(E): Lead the design and delivery of AI-powered products and subject matter depth in one or multiple key supply chain processes including demand planning, inventory optimization, procurement, logistics, and fulfillment, with understanding of underlying systems (e.g., ERP, MES, APS) and data (e.g., BOM, Orders, Inventory, etc.) . click apply for full job details
11/12/2026
Full time
Locations: Atlanta Austin Boston Brooklyn Chicago Dallas Denver Detroit Houston Miami Minneapolis Nashville New York Philadelphia Pittsburgh Durham Summit Washington Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. BCG's Tech and Digital Advantage (TDA) practice focuses on helping clients deliver competitive advantage and business superior performance through data, technology and digital. BCG Platinion sits within the TDA practice and is at the heart of the strategic impact we have with our clients. Our consultants and experts globally work across all industries and provide deep experience and expertise in a wide variety of topics including Tech Advisory and Delivery, Architecture, Enterprise Solutions and Packaged Software, Cybersecurity, and Technology Risk Management. Our Tech Advisory and Delivery Chapter within BCG Platinion helps clients solve some of their most challenging problems through the development of superior IT concepts and tech solutions. The ideal candidate is both passionate as a consultant and technologist, and can bring their expertise to help develop customized, innovative client solutions. Tech Advisory & Delivery Managers at BCG Platinion are: Technical experts. They are critical thinkers and have extensive IT expertise that drives innovation for our clients, rooted in practicality. Data-driven storytellers. They gather information, evaluate against their expertise and build clear, insightful paths for clients. Collaborative. They are interdisciplinary team players who seek alignment and establish relationships ranging from cross-functional stakeholder groups to existing teams. Comfortable with ambiguity. They know the path forward isn't always well-defined. They are comfortable and confident working through the unknown. Change agents. They know how to make change happen across an organization across all levels - from executives to individual contributors and IT practitioners. They can align and onboard teams to implement new processes and toolsets. They embrace complex challenges and guide an organization to optimize IT best practices. Influencers. They build strong relationships to build trust and influence stakeholders. They are able to effectively communicate across Business & IT stakeholders in order to influence positive change. AI and Agentic native. They are versed in the latest AI and Agentic technologies and methodologies and leverage them daily to deliver high impact outcomes and tackle difficult challenges. About BCG Platinion BCG Platinion's presence spans across the globe, with offices in Asia, Europe, and South and North America. We achieve digital excellence for clients with sustained solutions to the most complex and time-sensitive challenge. We guide clients into the future to push the status quo, overcome tech limitations, and enable our clients to go further in their digital journeys than what has ever been possible in the past. At BCG Platinion, we deliver business value through the innovative use of technology at a rapid pace. We roll up our sleeves to transform business, revolutionize approaches, satisfy customers, and change the game through Architecture, Cybersecurity, Digital Transformation, Enterprise Application and Risk functions. We balance vision with a pragmatic path to change transforming strategies into leading-edge tech platforms, at scale. What You'll Do As a manager, you'll be given end-to-end responsibility for the larger and more complex "modules" within a BCG project and begin to develop specialized knowledge to help you solve our clients' problems. You'll work on a variety of digital topics, applying generalist consulting skills to strategic digital & technology questions. Working together with clients to understand their issues, you'll create strategies for change, win buy-in for your recommendations, and collaborate with fellow BCGers to transform client potential into performance. Given your role in leading larger and more complex "modules", you will manage, support, and coach more junior team members in addition to also serving as an individual contributor yourself. Our consultants within the Tech & Digital Advantage (TDA) Chapter are an integral part of BCG's core consulting team; we work side-by-side with all practice areas to create value and competitive advantage for our clients. You'll help your clients answer questions such as "How will AI disrupt my business model?", "How can businesses use data and analytics to create highly personalized outreach delivered through a seamless omnichannel experience?", "How can I ship higher quality digital services to my customers faster by using agile?" and many more. You're Good At: At Platinion, we expect our consultants to be able to contribute and quickly get up to speed on a variety of topics to support the ever-changing demands of our clients. However, that broad ability to deliver needs to be grounded in deep technological knowledge in 2-3 of our primary areas of expertise such as; Expertise Supporting AI and digital transformation efforts by developing strategies around: AI and Agentic Platforms. Data and digital analytics platforms. Cloud infrastructure and technologies. Data management capabilities. Enterprise Tech Platforms. Business IT architecture. Software and product management (including Agile ways of working). Tech, Enterprise Architecture and Data governance. Experience with a wide breadth of tech / AI / digital offerings, including but not limited to: Developing roadmaps and current state assessments for IT and AI/Data organizations in large companies across various industries. Orchestrating technical program delivery across business stakeholders, complex vendor landscapes and technology ecosystems. AI / LLM cost optimization and FinOps. IT Benchmarking and recommendations for IT cost take-out initiatives. Developing future state tech vendor landscape, vendor assessments/selections automation, tech cost benefits analysis, eCommerce, platform valuation and design. Supporting tech functions during mergers and acquisitions, including the functional and technical transformation of an organization's IT department. Communicating the differences and benefits between multiple cloud computer providers and strategies for migrating from on-premise architecture. Utilizing working knowledge and experience with GenAI and its potential use cases and client implications to deliver both practical and visionary solutions. Experience leading the design and delivery of AI-powered products within a functional and/or industry business domain, including: Defining AI product vision, roadmaps, and prioritization frameworks grounded in domain-specific workflows and business value. Translating business strategy into AI-enabled product concepts, functional specifications, and delivery plans. Leading agile product delivery including sprint planning, backlog management, and iterative development across teams. Owning product quality assurance and ensuring outputs meet functional, technical, and compliance requirements as well as catch bad AI engineering. Defining product / solution architecture and data integration patterns. Designing and overseeing the integration of AI and generative AI capabilities into enterprise workflows at scale. Defining data strategy and governance requirements to underpin reliable, production-grade AI products. Leading the design of agentic workflows and automation use cases, balancing innovation with operational feasibility. Leading vendor evaluations and platform selection processes for AI product tooling, aligned to business and technical requirements. Driving change management and adoption strategies to embed AI products into business operations and ways of working. Optimizing business and IT processes within complex and heavily matrixed organizations and effectively communicating a path forward for clients and internal stakeholders. Delivering data and digital platforms using techniques such as Agile, DevSecOps, and Cloud native architectures. Specific AI product domain expertise topics (preferred): FP&A & FinOps: Lead the design and delivery of AI-powered products and subject matter depth in one or multiple core finance processes, including FP&A, financial close and reporting, procure to pay, order to cash, etc., with understanding of underlying finance systems (e.g. ERP, CLM, EPM, etc.) and data (e.g., GL, Orders, Invoices, Contracts, Plan/Forecast, etc.). Experience deploying AI use cases ranging from operational quick wins (e.g., AI chat enabled reporting insights) to strategic transformation (e.g., AI order-to-cash automation). Supply Chain / S&OP(E): Lead the design and delivery of AI-powered products and subject matter depth in one or multiple key supply chain processes including demand planning, inventory optimization, procurement, logistics, and fulfillment, with understanding of underlying systems (e.g., ERP, MES, APS) and data (e.g., BOM, Orders, Inventory, etc.) . click apply for full job details
