17 jobs found

Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar

Job Description Principal AI Solutions Architect About Us MathCo (TheMathCompany) is a global Enterprise AI and Analytics company trusted by Fortune 500 and Global 2000 enterprises for data-driven decision-making. Founded in 2016, MathCo builds custom AI and advanced analytics solutions focused on enterprise problem-solving through its innovative hybrid model. NucliOS, MathCo's proprietary platform with pre-built workflows and reusable plug-and-play modules, enables the vision of connected intelligence at a lower TCO. We foster an open, transparent, and collaborative culture with no barriers, making MathCo a great place to work. We offer exciting growth opportunities and value capabilities and attitude over experience-enabling our Mathemagicians to truly Leave a Mark. Role Overview We are seeking a Principal AI Solutions Architect with deep, hands-on experience building production GenAI and agentic systems. You will be the senior technical voice on our US AI engagements focused on AI-ready data and context foundations and on operating AI on an enterprise scale, across CPG, Retail, Life Sciences and other industries, turning that expertise into scalable applications that solve complex business problems. This is not a research role. We are looking for someone who has designed and implemented production AI solutions and knows what it takes to move from POCs to enterprise-scale applications. You will work on client opportunities from the first conversation through proposal, alongside our client and sales leaders, and with MathCo's global architecture and delivery teams, including our teams in India, so that every solution is technically sound and deliverable. The ideal candidate has worked deeply with LLMs, knowledge graphs, context engineering, agentic systems, AI orchestration, and modern AI and data platforms. What You'll Do Serve as a GenAI technical authority Provide senior technical credibility in strategic client and solutioning conversations with CTOs, CIOs, Chief Data Officers, AI leaders and business executives. Translate complex AI concepts into clear business implications, trade-offs and recommendations. Lead in-depth technical discussions on context layer, knowledge graphs, agents and AI operations in live client settings. Architect enterprise AI solutions Define end-to-end architectures that bring together LLMs, knowledge graphs, retrieval and context layers, agents, tools, orchestration frameworks and enterprise data. Develop architecture patterns that take AI applications from prototype to production. Evaluate options against business requirements, performance, scalability, security, maintainability and cost. Provide technical direction to engineering and delivery teams, and build a working prototype or demo when needed. Author and present the technical sections of proposals: architecture, phasing, assumptions and effort estimates. Build reusable reference architectures, scoping frameworks and platform-specific demos. Connect AI to business outcomes Work with clients to understand business processes and identify where AI can materially change how work gets done. Partner with business and consulting teams to shape AI opportunities into technically viable solutions. Build the business case: quantify the value and ROI of AI programs Design the data and context foundation Design how context is assembled and managed for AI systems across structured and unstructured enterprise knowledge. Design solutions using knowledge graphs, retrieval, memory, tools and other mechanisms that improve the relevance and reliability of LLM applications. Design the data foundation under AI applications: lakehouse and data-platform architecture, metadata and catalogs, semantic layers, data quality and access controls. Architect agentic systems, including tools, orchestration, guardrails and supporting infrastructure. Operationalize AI at enterprise scale Shape AI operations solutions: LLMOps, evaluation and monitoring, guardrails, and model and agent lifecycle management. Advise on AI cost: token usage and optimization, model selection and routing, and infrastructure trade-offs. Advise on AI governance and risk, including frameworks such as NIST AI RMF and the EU AI Act, data privacy (including HIPAA), security and audit. Develop points of view on emerging AI-at-scale topics with MathCo's innovation teams. What We're Looking For 10+ years in AI, machine learning, data or enterprise architecture, including 2+ years designing and shipping production GenAI / LLM applications. Hands-on experience building sophisticated AI applications with commercial and/or open-source foundation models. Strong knowledge of LLM application architecture, context engineering, knowledge graphs, retrieval and grounding, agentic AI and multi-step workflows, AI orchestration, and enterprise data integration. Working knowledge of lakehouse and data platforms (e.g., Databricks, Snowflake, BigQuery), semantic layers, metadata and catalogs. Working knowledge of evaluation, observability and LLMOps, AI cost optimization, and AI governance, privacy and security. Familiarity with leading model ecosystems (OpenAI, Anthropic, Google) and hyperscaler AI services Pre-sales, solutions engineering or consulting experience, including authoring and defending the technical sections of proposals and SOWs. Ability to explain why specific technical choices were made, to engineers and executives alike. Experience working with global delivery teams across time zones. Exposure to data and AI use cases in CPG, Retail or Life Sciences. What Will Differentiate You The strongest candidates will be able to demonstrate all three of the following: 1. Technical depth You understand the mechanics of modern AI systems deeply enough to engage with senior AI engineers, scientists and architects. 2. Architecture and implementation experience You can whiteboard an end-to-end AI architecture and explain how it would actually be implemented, including the decisions and trade-offs required to make it successful at enterprise scale. 3. Executive and client credibility You can take that same architecture into a client conversation and explain it in a way that builds confidence with both business and technical executives - including a value case a CFO would sign off on. What Success Looks Like You are the trusted technical voice on our AI data, context and scale engagements. Your proposal architectures are credible, clearly scoped and deliverable. The reference architectures, ROI models and demos you build are used across the team. You bring new points of view on operating AI at scale to our clients. Being a Mathemagician Embody MathCo's values of openness, ownership, and impact. Contribute actively to internal mentorship, innovation, and team development. Champion diversity, equity, and inclusion by valuing a variety of perspectives in problem-solving. Why Join Us? MathCo is recognized globally as a leader in enterprise AI and analytics: Leader in Generative AI Service Providers - PeMa Quadrant (AIMResearch) Named among North America's Inspiring Workplaces Accredited for Inclusive Practices - Great Place to Work Institute, India Recognized for DEIB Excellence - India's Best Workplaces for DEIB To learn more, visit

Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Principal AI Engineer provides the highest level of individual-contributor technical leadership for the company's AI platform, operating one level above the Lead AI Engineer role. This person sets the multi-year architecture strategy for agentic and LLM-powered systems - spanning model strategy, retrieval-augmented generation (RAG), tool/connector ecosystems, and evaluation/governance tooling - across every team that builds on the AI platform, not just one. In a highly regulated healthcare environment, the Principal AI Engineer resolves the hardest, most ambiguous technical problems facing the platform, is a primary technical voice with executive leadership on AI strategy and risk, and shapes how the entire engineering organization adopts AI safely and effectively. Success is measured by the durability and adoption of the technical strategy this role sets across multiple teams, this role's ability to unblock cross-organizational technical risk before it becomes a delivery or compliance problem, and its influence on AI investment decisions at the executive level. Key Responsibilities Enterprise AI Strategy: Own the multi-year technical strategy and roadmap for the AI platform across all teams building on it, not a single product or team - model strategy, RAG/retrieval architecture, connector ecosystems, and evaluation frameworks. Technical Authority: Serve as the final technical escalation point for the hardest, most ambiguous architecture and reliability problems on the AI platform, spanning multiple teams and systems. Cross-Team Standards: Set architecture, security, and evaluation standards that multiple Lead AI Engineers and their teams adopt; audit and evolve those standards as the platform and threat landscape change. Executive Advisory: Serve as a primary technical voice to VP- and executive-level leadership on AI platform strategy, model risk, and investment trade-offs. Deep Technical Delivery: Personally lead architecture and prototyping for the organization's highest-ambiguity, highest-risk AI initiatives - the problems no existing team or pattern already solves. Mentorship at Scale: Develop Lead and Senior AI Engineers into stronger technical leaders through design review, technical coaching, and structured knowledge-sharing across teams. Responsible AI & Governance: Shape enterprise-wide AI governance policy - model risk review, connector/tool approval frameworks, and PHI-handling standards - in partnership with Legal/Compliance/Privacy leadership. Vendor & Model Strategy at Scale: Own evaluation and long-term strategy for foundation model providers and AI infrastructure vendors across the company, not just a single team's stack. External Technical Representation: Represent the company's AI engineering capability externally - industry forums, partner/vendor technical relationships, and recruiting for senior technical talent. Organizational Impact: Influence AI platform direction and investment across the broader enterprise, extending beyond a single business unit. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role, presently or in the future. Minimum Requirements Bachelor's degree or equivalent experience; typically 12+ years of software engineering experience, including 6+ years focused on AI/ML, LLM, or NLP systems in production and 3+ years operating as a senior individual-contributor technical leader. Fewer years required with a relevant Master's or Doctorate. Critical Skills One level of demonstrated technical leadership above a Lead AI Engineer - e.g., setting technical direction and standards across multiple teams, not just owning architecture for a single team or platform area. Proven track record setting technical strategy that multiple teams adopt, not just delivering within one team's roadmap. Deep, hands-on expertise building production LLM applications at scale: prompt engineering, RAG, agentic workflows, tool use, and evaluation harnesses - with the judgment to know which patterns will and won't hold up over multiple years. Experience with commercial large language model APIs (e.g., Anthropic, OpenAI) and tool-integration protocols such as Model Context Protocol (MCP), including evaluating emerging alternatives. Strong software engineering fundamentals: Python and/or Java, REST APIs, event-driven architecture, microservices, and cloud-native design (Azure preferred; AWS/GCP acceptable). Experience with vector/graph retrieval systems, embeddings, and knowledge-base architectures at production scale across multiple products. Deep working knowledge of LLMOps/MLOps: usage attribution, cost/spend monitoring, abuse detection, and model evaluation pipelines, including designing these systems from scratch. Demonstrated ability to influence and align senior engineering and executive stakeholders without direct authority. Deep familiarity with regulated/healthcare data environments and AI governance frameworks (model risk review, connector approval tiers, PHI handling). Preferred Qualifications Advanced degree (M.S. or Ph.D.) in Computer Science, AI/ML, or a related technical field. Prior experience as a Principal, Staff, or Distinguished Engineer setting AI/ML technical strategy across multiple teams inside healthcare IT or another highly regulated industry. Track record of publications, patents, open-source contributions, or industry speaking on applied AI/LLM systems. Experience shaping enterprise-wide AI governance policy in partnership with Legal, Compliance, and Privacy leadership. Additional Skills Deep awareness of the fast-moving GenAI/agentic landscape and a demonstrated ability to separate durable technical bets from hype. Experience managing strategic relationships with AI infrastructure vendors and model providers at the enterprise level. Exceptional written and verbal communication for executive, board-level, and external technical audiences. We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $195,000 - $325,000 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. About the Team Our AI Enablement team drives enterprise-wide adoption of generative AI, spanning platform engineering, governance, and hands-on delivery of AI-powered products and internal tooling. The team builds and operates the infrastructure, integrations, and knowledge systems that let engineering and business teams safely adopt large language models at scale. The Lead AI Engineer joins as the senior technical authority on this team, setting the architectural direction that Senior and Associate AI Engineers build against. Position Summary The Lead AI Engineer provides technical leadership and architecture ownership for the company's AI platform and its embedded delivery initiatives, operating one level above the Senior AI Engineer role. This person owns the technical design of agentic and LLM-powered systems built on large language model APIs, including retrieval-augmented generation (RAG), tool/connector integration, and evaluation/governance tooling, in a highly regulated healthcare environment. The Lead AI Engineer sets architectural standards across AI-embedded product delivery, mentors Senior and Associate AI Engineers, and represents AI platform architecture to engineering leadership and Legal/Compliance/Privacy. Success is measured by the reliability, security, and scalability of the AI systems shipped, the rate at which Senior/Associate engineers adopt the architectural standards this role sets, and this role's influence on AI platform decisions across the organization. Key Responsibilities AI Architecture Leadership: Define the technical architecture and roadmap for LLM/agentic systems - model routing across cloud AI platforms, connector/integration patterns, RAG pipelines, and prompt/evaluation frameworks. Solution Design & Governance: Lead architecture reviews for new AI capabilities and ensure designs meet enterprise security, privacy, and data-provenance requirements. Platform Ownership: Drive the technical design of shared AI platform capabilities, including knowledge-retrieval systems, citation/traceability of AI-generated outputs, and permission-aware access to data. Hands-On Delivery: Personally architect and build high-complexity components on priority AI delivery initiatives where a working system, not just a design doc, is the deliverable. Technical Mentorship: Set coding, architecture, and evaluation standards for Senior and Associate AI Engineers; run design reviews and pair on complex agentic workflows. LLMOps & Responsible AI: Establish secure, observable, and cost-attributed AI operations - usage/spend attribution, abuse monitoring, model evaluation, and rollback strategy - for production LLM systems. Cross-Functional Architecture: Partner with engineering managers, product, platform, and Legal/Compliance to align AI architecture decisions with delivery timelines and enterprise standards. Vendor & Model Strategy: Evaluate foundation model providers and AI tooling vendors; make build-vs-buy and model-selection recommendations. Compliance & Risk: Ensure AI systems handling protected health information (PHI) meet regulatory and enterprise governance requirements. Organizational Impact: Represent AI architecture in cross-company forums and influence enterprise-wide AI platform direction. Priority will be given to candidates who reside in the Columbus, OH metropolitan area. We are unable to provide sponsorship for this role, presently or in the future. Minimum Requirements Bachelor's degree or equivalent experience; typically 8+ years of software engineering experience, including 3+ years focused on AI/ML, LLM, or NLP systems in production. Fewer years required with a relevant Master's or Doctorate. Critical Skills One level of demonstrated technical leadership above a Senior AI Engineer - e.g., owning architecture for a team or platform area, not just a single feature. Deep, hands-on expertise building production LLM applications: prompt engineering, RAG/GraphRAG, agentic workflows, tool use, and evaluation harnesses. Experience with commercial large language model APIs (e.g., Anthropic, OpenAI) and tool-integration protocols such as Model Context Protocol (MCP). Strong software engineering fundamentals: Python and/or Java, REST APIs, event-driven architecture, microservices, and cloud-native design (Azure preferred; AWS/GCP acceptable). Experience with vector/graph retrieval systems, embeddings, and knowledge-base architectures at production scale. Working knowledge of LLMOps/MLOps: usage attribution, cost/spend monitoring, abuse detection, and model evaluation pipelines. Ability to set architectural standards and mentor other engineers through design review and pairing, not just documentation. Familiarity with regulated/healthcare data environments and AI governance frameworks (model risk review, connector approval tiers, PHI handling) is a plus. Preferred Qualifications Advanced degree (M.S. or higher) in Computer Science, AI/ML, or a related technical field. Prior experience leading AI/ML platform or applied-AI teams inside healthcare IT or another highly regulated industry. Experience modernizing legacy systems toward AI-embedded workflows (agent-assisted development, AI-powered risk scoring, AI-driven automation). Experience with Confluence/Jira-based engineering governance and enterprise architecture review boards. Additional Skills Strong awareness of the fast-moving GenAI/agentic landscape and a demonstrated habit of continuous learning. Experience managing relationships with AI tooling vendors and model providers. Clear written and verbal communication for both technical and executive audiences We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $155,300 - $258,800 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson's (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: . McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson's full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) or (Canada) . Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

This job is with Allianz Commercial, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly. The Data & Analytics Platforms Team (DAP) develops and runs central platforms and data products, which enable the Allianz Operating Entities (OEs) to generate value from data & analytics at scale. The major offering is the Allianz Data Platform (ADP) - a PaaS offering -, which comprises necessary capabilities to store, transfer and analyze data, as well as running data & analytics products. In addition, ADP also serves capabilities for ML (ops) and GenAI / Agentic AI use cases. The Data Architect (hands on) will be responsible to shape the future ADP data offering (evaluate, design and implement technical platform capabilities), spanning data storage, data modeling, data integration, and analytics enablement. Moreover, they will advice local implementation teams how to best apply platform capabilities for effective / efficient local application built / use case implementation. The candidate should bring a deep understanding of data architecture (data modeling, data warehousing, and data governance), market leading data platform solutions (e.g. Databricks) and modern data engineering technologies. What you do (Hands on Data architect) Data Platform Strategy: Lead the migration of data workloads and data stores from on-premises infrastructure to MS Azure Cloud, ensuring alignment with Allianz's cloud strategy. Design, build, and test data architectures in an enterprise setup to ensure efficient transfer and storage of large amounts of data, maintaining information accuracy and security during data transfers. Stay updated with developments in data management, data platforms, and data engineering, providing guidance to cross-functional teams on data access and data integration, especially during major transfers, updates, or changes. Architecture Design: Develop and oversee data architecture designs that meet business requirements and strategic objectives. Ensure solutions are scalable, secure, and cost-effective. Act as a thought leader and expert on data modeling, data integration, and Data Platform capabilities, advising customers and internal teams on the latest technology and valuable implementation strategies within Allianz. Leverage data and analytics capabilities to create high-performing data services within the existing landscape, troubleshooting and solving technical issues with creativity and prior knowledge. Stakeholder Engagement: Collaborate with enterprise architects, area architects, and business requirement teams to ensure solutions meet business needs and strategic goals. Technical Leadership: Provide guidance and mentorship to junior architects and technical teams, fostering a culture of innovation and continuous improvement. Serve as the Data architect subject-matter expert for the entire department, offering strategic insights and leadership. Documentation and Compliance: Ensure thorough documentation of architecture designs and processes, maintaining compliance with Allianz standards and policies. Ensure adherence to industry standards and best practices in all processes, fostering innovation and efficiency in data management. Value Proposition: Drive initiatives that enhance the value proposition of Allianz's data solutions, focusing on expanding service capabilities and integrating new functionalities. Vet data platform providers and third-party services to ensure high-quality offerings for storage, compute, and data processing, while creating standard operating procedures and policy documentation for data transfer and storage. What you bring (Hands on Data architect) Bachelor's degree in Computer Science, Information Systems, or a related field. 8-10 years experience required with five years' experience as a Data Architect or similar role. Deep understanding of data architecture concepts, data modeling techniques, and data platform frameworks, with proficiency in designing and implementing data solutions that align with business objectives using popular platforms like Azure, and AWS . Knowledge of data platform engineering, data warehousing, and data lake / lakehouse design, with experience using major cloud computing services such as Microsoft Azure, Oracle Cloud Infrastructure (OCI), and Amazon Web Services (AWS). Ability to design scalable and robust enterprise architectures that integrate data pipelines and data technologies into existing systems, identifying integration points and ensuring interoperability with other enterprise applications, databases, and services. Strong data migration and data management skills, emphasizing data privacy and security, along with excellent problem-solving capabilities in a fast-paced work environment. Strong communication skills and willingness to collaborate with cross-functional departments and teams. Relevant industry certifications, such as Databricks, Microsoft Azure, or AWS, are highly desirable; proficiency in English is required. Experience with hybrid cloud environments. Familiarity with enterprise architecture and innovation strategies. Ability to work collaboratively in a dynamic, cross-functional environment. Knowledge of data governance, data quality, and metadata management Preferred business domain: Business knowledge of Life insurance domain What we offer We offer a hybrid work model which recognizes the value of striking a balance between in-person collaboration and remote working We believe in rewarding performance and our compensation and benefits package includes health insurance, company bonus scheme, 401(K) with company match, company paid holidays, paid time off, paid volunteer days, tuition reimbursement, paid parental leave, an employee shares program and employee discounts From career development and digital learning programs to international career mobility, we offer lifelong learning for our employees worldwide and an environment where innovation, delivery and empowerment are fostered. The annualized base pay range for this role is $110,000 - 150,000. The annual base salary range represents a nationwide market range. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role, and the skills, education, training, credentials and experience of the candidate. The base pay is just one component of the ATA total compensation package. As part of our comprehensive compensation and highly rated benefits programs, ATA also offers eligibility for an incentive-based annual bonus. About Allianz Technology Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges is what makes us a unique employer. We are united by a shared commitment: to put our customers first and at the centre of everything we do. Their needs inspire our thinking and guide our actions. Together, we can build an environment where everyone feels empowered and confident to explore, grow and shape a better future - for our customers and for the world around us. At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. The foundation for this is our inclusive workplace, where people and performance both matter, and where integrity, fairness, inclusion and trust are at the heart of our culture. We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations. Join us. Let's care for tomorrow. You.IT

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

Candidates must be authorized to work in the United States without the need for current or future visa sponsorship. This position is for full-time, onsite employment at the Family Dollar Chesapeake, VA Store Support Center. We handle relocation for anyone interested outside of the Hampton Roads, VA area General Summary: The AI Lead Developer is a hands-on "builder" role, and a senior technical staff engineer who can lead a team of developers and can also builds new AI applications and software including agentic AI applications, analytical solutions and pilot new ideas from incubation to deployment. This role is a critical part of Family Dollar's capability to build our own AI applications inhouse using top of line agent development kits, APIs, software libraries and interface with our vendors and partners to trial their products for fit within Family Dollar's IT estate, including our cloud environments, digital applications, and our operational systems. This position is fully onsite. Principal Duties & Responsibilities: Translate business requirements into target AI solutions that can be delivered fast and iteratively on Google Cloud Platform. Develop agentic AI applications using modern agent development kits and frameworks (e.g., Google Agent Development Kit, Gemini Agent Platform, LangGraph, etc), including multi-agent workflows, tool integration, and human-in-the-loop checkpoints. Build and operate retrieval-augmented generation (RAG) solutions that ground LLMs in Family Dollar's enterprise data, including ingestion, embeddings and vectors. Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution. Establish and maintain MLOps and CI/CD pipelines for AI workloads, including model and prompt versioning, evaluation harnesses, monitoring, cost controls, and rollback procedures. Implement enterprise-grade guardrails for AI applications, prompt-injection defense, PII handling, content safety, role-based access controls, and audit logging; partnering with platform, security, infrastructure, and business stakeholders to meet Family Dollar's standards for identity, networking, data residency, and compliance. Define how AI applications integrate into Family Dollar's existing IT estate. Set integration patterns, APIs, and data contracts across identity, networking, data, and retail systems (POS, ERP, CRM, inventory, supply chain), partnering with the teams that own those systems. Own technical quality across the team's AI work - set and uphold engineering standards, review code, and keep technical debt low so solutions stay maintainable and easy to operate Partner with IT support to transition support gradually through SOPs, runbooks, dashboards, on-call coverage, and alerting, and escalation point after handover. Lead and mentor the engineering team, sharing knowledge and setting technical standards across the AI and Automation team. On call coverage (technical support) as needed. Performs other duties as assigned. Position Requirements: Fully onsite office work environment Minimum Requirements: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred). 5+ years of progressive IT experience in large, cross-functional teams or projects, preferably in a retail environment. 2+ years developing AI solutions in a leading role Write clean, well-tested, well-documented code; conduct code reviews; and contribute to internal libraries, templates, and engineering best practices. Sense of urgency and the ability to drive a delivery team toward results in a dynamic environment. Ability in developing, presenting and communicating technical concepts to varying audiences Experience in retail, supply chain, or large-scale operational environments within retail systems (POS, ERP, CRM, inventory, supply chain, etc). Advanced knowledge of recent GenAI platform advancements. Experience in Google Cloud Platform, generative AI, LLMs, and agentic frameworks "Projected Salary Range: $132,000 to 160,000". 20% annual bonus opportunity plus other incentives Family Dollar is an equal opportunity employer and committed to recruiting, hiring, training, and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We are committed to complying with the Americans with Disabilities Act (ADA) and providing reasonable accommodations to qualified individuals with disabilities. Full time 510 Volvo Parkway,Chesapeake,Virginia 23320 IT Development Family Dollar

AI Engineer 5 (GenAI Platform, Agentic Infrastructure) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

AI Engineer 5 (GenAI Platform, Agentic Infrastructure) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

AI Engineer 5 (GenAI Platform Services, Agentic Platform) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

AI Engineer 5 (GenAI Platform Services, Agentic Platform) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

Job Description Job Description H2O.ai is on a mission to democratize AI for Good. As the world's leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purpose-built Agents, SLMs, and solutions on their private data. With a focus on secure, compliant, and infrastructure-flexible Sovereign AI deployments, H2O.ai delivers solutions that align with the highest standards of data privacy and control. Its open-source technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune 500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH. For more information, visit . About This Opportunity We are looking for a Principal AI Engineer who builds things that matter. You will design and ship end-to-end AI solutions for some of APAC's most complex enterprise problems - spanning agentic AI systems, LLM applications, and production ML pipelines. This is a hands-on engineering role embedded within a customer-facing field team, meaning your work will be seen, used, and evaluated by real enterprises from day one. You will work alongside Kaggle Grandmasters, ML engineers, and domain experts to deliver AI that goes beyond demos - into production, into workflows, and into measurable business outcomes. This position is based in Dallas, Texas and requires onsite customer interfacing. What You Will Do Customer Engagement Leadership Lead end-to-end technical engagement with enterprise customers, acting as the senior point of accountability for delivery quality, stakeholder relationships, and outcomes. Manage multiple concurrent engagement streams simultaneously - coordinating workplans, resourcing, and milestones across cross-functional teams. Serve as the primary technical escalation point for customer issues, proactively identifying risks and driving resolution across engineering, product, and leadership. Build and maintain trusted relationships with customer data science teams, engineering leads, and executive stakeholders - translating business needs into technical direction and back again. Lead pre-sales and proof-of-concept engagements, setting the technical strategy and ensuring the team delivers demonstrations that build genuine enterprise trust. Represent H2O.ai externally at customer workshops, executive briefings, and technical deep-dives as a credible senior voice. Agentic AI & LLM Engineering Design and build agentic AI systems and multi-agent frameworks that automate complex, multi-step enterprise workflows. Develop and deploy LLM-powered applications using RAG, fine-tuning, prompt engineering, function calling, and tool use. Implement guardrails, evaluation frameworks, and responsible AI controls to ensure production-grade reliability and safety. Stay current with the rapidly evolving agentic AI landscape - MCP, LLM orchestration frameworks, reasoning models - and bring the best into customer engagements. End-to-End AI Application Development Own the full development lifecycle across multiple streams: from problem framing and data exploration through model development, API integration, and production deployment. Build scalable backend services and APIs that expose AI capabilities to enterprise applications and workflows. Integrate AI models into customer environments - cloud, on-prem, and hybrid - ensuring performance, stability, and maintainability at scale. Develop ML pipelines and LLMOps infrastructure that support continuous model improvement and monitoring in production. Team Collaboration & Delivery Excellence Coordinate delivery across engineers, program managers, and solution architects - ensuring workstreams are aligned, unblocked, and progressing to plan. Set the technical bar for the engagements you lead, reviewing outputs, shaping architecture decisions, and ensuring engineering quality across the team. Mentor and guide junior ML engineers and solution engineers within engagements, building team capability alongside delivery. Collaborate closely with H2O.ai product and engineering teams to surface customer feedback, shape roadmap input, and resolve platform-level issues. What We Are Looking For Experience & Background 8+ years of hands-on AI/ML engineering experience, including end-to-end model development and production deployment. Demonstrable experience leading technical delivery across complex, multi-stakeholder enterprise engagements - not just executing within them. Demonstrable experience building LLM-powered applications - RAG pipelines, agentic workflows, fine-tuned models, or similar. Strong Python engineering skills; experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and LLM tooling (LangChain, LlamaIndex, or equivalent). Experience deploying AI services in cloud or enterprise environments (AWS, Azure, GCP, on-prem Kubernetes). Skills & Capabilities Proven ability to manage multiple concurrent workstreams and coordinate cross-functional teams toward shared delivery milestones. Deep understanding of modern GenAI concepts: prompt engineering, RAG, fine-tuning, RLHF, model evaluation, guardrails, and LLMOps. Solid grounding in classical ML - able to select the right tool for the problem, not just default to the latest LLM. Backend development skills: REST APIs, containerisation (Docker/Kubernetes), and CI/CD pipelines for AI applications. Strong executive communication - able to run a board-level briefing one hour and a technical design review the next, credibly. Comfortable with ambiguity and able to set direction for a team when requirements are incomplete or evolving. How to Stand Out From the Crowd Kaggle or competitive ML experience. Familiarity with H2O.ai products, Wave, or H2O Document AI. Experience in financial services, healthcare, or other regulated industry AI deployments. Exposure to tabular foundation models, AutoML, or enterprise ML platforms. Prior experience in a customer-facing or field engineering role. Why H2O.ai? Market leader in total rewards Remote-friendly culture Flexible working environment Be part of a world-class team Career growth The base salary for this role ranges from $175,000 to $200,000. Compensation is determined based on several factors, including skills, experience, job scope, location, and relevant market compensation data. H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis. H2O.ai is an innovative AI cloud platform company, leading the mission to democratize AI for everyone. Thousands of organizations from all over the world have used our cutting-edge technology across a variety of industries. We've made it easy for people at all levels to generate breakthrough solutions to complex business problems and advance the discovery of new ideas and revenue streams. We push the boundaries of what is possible with artificial intelligence. H2O.ai employs the world's top Kaggle Grandmasters, the community of best-in-the-world machine learning practitioners and data scientists. A strong AI for Good ethos and responsible AI drive the company's purpose. Please visit to learn more.

AI Engineer 5 (GenAI Platform Services, Agentic Platform) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

AI Engineer 5 (GenAI Platform Services, Agentic Platform) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

AI Engineer 5 (GenAI Platform, Agentic Infrastructure) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details

AI Engineer 5 (GenAI Platform, Agentic Infrastructure) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. What You'll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java Preferred Qualifications: Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Experience designing, developing, delivering, and supporting complex AI systems 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 Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost Experience in building agentic AI systems and agentic workflows Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) 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. Cambridge, MA: $229,900 - $262,400 for AI Engineer 5 McLean, VA: $229,900 - $262,400 for AI Engineer 5 New York, NY: $250,800 - $286,200 for AI Engineer 5 San Francisco, CA: $250,800 - $286,200 for AI Engineer 5 San Jose, CA: $250,800 - $286,200 for AI 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 . click apply for full job details