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%
LexisNexis Legal & Professional
Horsham, Pennsylvania
This job is with LexisNexis Legal & Professional , 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 Our Team For over 50 years, LexisNexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) to deliver secure, scalable, and high-quality patent data processing solutions. Our work transforms complex, unstructured patent submissions into standardized, searchable outputs that power examiner workflows and public dissemination. We operate in a highly regulated environment with strict security requirements, large-scale data volumes, and complex business rules. Our focus is on modernizing legacy workflows through automation, AI, and platform transformation to improve efficiency, accuracy, and cost effectiveness. About the Role Principal AI Engineer - Architecture Track We are seeking a hands-on Principal AI Engineer who can design and build production-grade AI solutions while growing into a broader AI Architect role. This position is ideal for an experienced AI developer or technical lead who has strong engineering depth, understands modern AI architecture, and is ready to expand their influence across platforms, products, and delivery teams. The Principal AI Engineer will work closely with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities. The role will initially focus on solution design and hands-on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross-team alignment. Conditions of Employment: You must be a U.S. citizen to apply for this position. You must successfully pass a background investigation and achieve Public Trust security clearance. Must be located near the Horsham, PA location for a hybrid onsite schedule. Responsibilities AI Solution Design and Development Design, prototype, and implement AI-powered applications, services, agents, and workflows. Translate business, user, and government mission requirements into practical technical solutions. Develop solutions using large language models, retrieval-augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies. Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations. Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications. Balance rapid experimentation with the engineering discipline required for secure, reliable production systems. Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit. Architecture and Technical Leadership Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring. Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures. Help teams make informed decisions regarding commercial, open-source, and internally developed AI capabilities. Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies. Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks. Provide technical guidance, code reviews, mentoring, and hands-on support to engineering and data science teams. Grow into ownership of end-to-end AI solution architecture and broader technical strategy. Government and Stakeholder Engagement Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses. Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non-technical audiences. Help move successful prototypes into secure, supportable, and scalable production capabilities. Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations. Requirement Bachelor's degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience. Significant professional software engineering experience, including experience delivering production applications or platforms. Hands-on experience developing AI, machine-learning, or data-intensive solutions. Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control. Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents. Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices. Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs. Experience working across product, engineering, data, security, and business teams. Strong written and verbal communication skills. Ability to satisfy applicable government background, suitability, or contractual requirements. Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs. Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability. Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability. Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle. Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements. Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI. Preferred Qualifications Experience delivering technology solutions for U.S. federal, state, or local government customers. Experience working in government contracting, regulated environments, or programs involving sensitive data. Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls. Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud. Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps. Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices. Experience moving AI proofs of concept into production. Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops. Prior technical leadership, mentoring, or architecture-review experience. Relevant cloud, architecture, security, data, or AI certifications. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working flexible hours to help you fit everything in and work when you are the most productive Working for You We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits Health Savings, Health Care, Dependent Care and Commuter Spending Accounts Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process . click apply for full job details
11/14/2026
Full time
This job is with LexisNexis Legal & Professional , 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 Our Team For over 50 years, LexisNexis Reed Technology has partnered with the U.S. Patent and Trademark Office (USPTO) to deliver secure, scalable, and high-quality patent data processing solutions. Our work transforms complex, unstructured patent submissions into standardized, searchable outputs that power examiner workflows and public dissemination. We operate in a highly regulated environment with strict security requirements, large-scale data volumes, and complex business rules. Our focus is on modernizing legacy workflows through automation, AI, and platform transformation to improve efficiency, accuracy, and cost effectiveness. About the Role Principal AI Engineer - Architecture Track We are seeking a hands-on Principal AI Engineer who can design and build production-grade AI solutions while growing into a broader AI Architect role. This position is ideal for an experienced AI developer or technical lead who has strong engineering depth, understands modern AI architecture, and is ready to expand their influence across platforms, products, and delivery teams. The Principal AI Engineer will work closely with product managers, architects, data scientists, software engineers, security teams, and government stakeholders to translate mission and business needs into secure, scalable, and reusable AI capabilities. The role will initially focus on solution design and hands-on implementation, with increasing responsibility for architecture standards, technical strategy, governance, and cross-team alignment. Conditions of Employment: You must be a U.S. citizen to apply for this position. You must successfully pass a background investigation and achieve Public Trust security clearance. Must be located near the Horsham, PA location for a hybrid onsite schedule. Responsibilities AI Solution Design and Development Design, prototype, and implement AI-powered applications, services, agents, and workflows. Translate business, user, and government mission requirements into practical technical solutions. Develop solutions using large language models, retrieval-augmented generation, machine learning, natural language processing, computer vision, or other relevant AI technologies. Build reusable AI components, services, APIs, evaluation frameworks, and reference implementations. Integrate AI capabilities with enterprise platforms, data sources, workflows, and existing applications. Balance rapid experimentation with the engineering discipline required for secure, reliable production systems. Evaluate models, platforms, frameworks, and vendors based on performance, cost, security, scalability, and mission fit. Architecture and Technical Leadership Contribute to solution architectures covering applications, models, data, integrations, infrastructure, security, and operational monitoring. Partner with senior architects to establish AI architecture patterns, guardrails, standards, and reference architectures. Help teams make informed decisions regarding commercial, open-source, and internally developed AI capabilities. Identify opportunities to create shared AI services and reusable capabilities across products, contracts, and government agencies. Participate in architecture reviews and clearly document technical decisions, tradeoffs, assumptions, and risks. Provide technical guidance, code reviews, mentoring, and hands-on support to engineering and data science teams. Grow into ownership of end-to-end AI solution architecture and broader technical strategy. Government and Stakeholder Engagement Support technical discovery sessions, demonstrations, proofs of concept, proposals, RFIs, and RFP responses. Communicate complex AI concepts, limitations, risks, and tradeoffs clearly to both technical and non-technical audiences. Help move successful prototypes into secure, supportable, and scalable production capabilities. Stay informed about evolving government AI policies, standards, acquisition practices, and responsible-AI expectations. Requirement Bachelor's degree in computer science, engineering, data science, information systems, or a related field, or equivalent practical experience. Significant professional software engineering experience, including experience delivering production applications or platforms. Hands-on experience developing AI, machine-learning, or data-intensive solutions. Proficiency in Python and experience with APIs, cloud services, data pipelines, software development practices, and source control. Experience with modern generative-AI patterns, such as large language models, retrieval-augmented generation, embeddings, vector search, tool use, structured outputs, or AI agents. Understanding of cloud-native architecture, system integration, identity and access management, observability, and secure development practices. Ability to evaluate technical alternatives and explain architecture decisions and tradeoffs. Experience working across product, engineering, data, security, and business teams. Strong written and verbal communication skills. Ability to satisfy applicable government background, suitability, or contractual requirements. Incorporate security, privacy, accessibility, explainability, auditability, and human oversight into solution designs. Establish appropriate evaluation methods for accuracy, relevance, groundedness, bias, safety, and reliability. Design controls for model and prompt versioning, data lineage, access management, logging, monitoring, and traceability. Partner with cybersecurity, legal, privacy, compliance, and governance teams throughout the solution lifecycle. Ensure solutions align with applicable organizational policies, contractual obligations, and government requirements. Design human-in-the-loop controls based on the risk and impact of the decisions supported or performed by AI. Preferred Qualifications Experience delivering technology solutions for U.S. federal, state, or local government customers. Experience working in government contracting, regulated environments, or programs involving sensitive data. Familiarity with government security and compliance frameworks, such as NIST, FedRAMP, FISMA, or agency-specific controls. Experience with one or more major cloud platforms, particularly AWS, Microsoft Azure, or Google Cloud. Experience with AI orchestration frameworks, model gateways, vector databases, evaluation platforms, MLOps, or LLMOps. Understanding of model evaluation, prompt engineering, fine-tuning, data governance, and responsible-AI practices. Experience moving AI proofs of concept into production. Experience supporting technical proposals, RFIs, RFPs, solution demonstrations, or customer workshops. Prior technical leadership, mentoring, or architecture-review experience. Relevant cloud, architecture, security, data, or AI certifications. Work in a Way That Works for You We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. Working flexible hours to help you fit everything in and work when you are the most productive Working for You We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits Health Savings, Health Care, Dependent Care and Commuter Spending Accounts Up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice About the Business LexisNexis Legal & Professional provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision-making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis and Nexis services. U.S. National Base Pay Range: $136,100 - $252,800. Geographic differentials may apply in some locations to better reflect local market rates. This job is eligible for an annual incentive bonus. We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process . click apply for full job details
Senior Manager, Machine Learning Engineer (People Leader) 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 Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community 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 At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 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 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 Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer 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
Senior Manager, Machine Learning Engineer (People Leader) 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 Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community 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 At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 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 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 Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer 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).
Senior Manager, Machine Learning Engineer (People Leader) 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 Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community 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 At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 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 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 Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer 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
Senior Manager, Machine Learning Engineer (People Leader) 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 Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers Recruit, nurture, and retain top engineering talent Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community 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 At least 1 year of people leadership experience Preferred Qualifications: Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field 3+ years of experience managing and leading an ML engineering team 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 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 Sr. Manager, Machine Learning Engineer New York, NY: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer Plano, TX: $209,000 - $238,500 for Sr. Manager, Machine Learning Engineer San Francisco, CA: $250,800 - $286,200 for Sr. Manager, Machine Learning Engineer 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 H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
09/28/2026
Full time
Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.
