Director AI Engineer

Capital One • San Jose, CA

2d • $293,600 - $335,100

About The Position

Capital One is hiring a Director AI Engineer to help build responsible, reliable, and scalable AI systems that improve how associates work and customers interact with the company. The role is part of the Intelligent Foundations and Experiences team, which partners across Capital One to advance AI science and engineering and build proprietary solutions used across the business.

The Director partners with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products. The role oversees the design, development, testing, deployment, and support of AI software, contributes to the technical vision and long-term roadmap for foundational AI systems, and makes build-versus-buy decisions across open-source and SaaS AI technologies. It also advances optimization techniques for production systems and translates enterprise AI strategy into portfolio-level execution across multiple product areas.

The position includes people leadership: attracting and retaining talent, mentoring and developing team members, and fostering a learning culture. The Director scales AI engineering practices through shared infrastructure, reusable components, observability, and governance frameworks; establishes Responsible AI standards; and partners with research, compliance, and enterprise risk teams to address ethical and regulatory expectations.

Requirements

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field and at least 8 years of experience developing AI and ML algorithms or technologies; or a master’s degree in one of those fields and at least 6 years of such experience.
• At least 3 years of people leadership experience.

Nice To Haves

• 5 or more years of experience managing and leading an engineering team.
• 7 or more years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• Experience developing AI and ML algorithms or technologies, such as LLM inference, similarity search and VectorDBs, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Golang.
• Experience building agentic AI systems and agentic workflows.
• Passion for keeping abreast of AI research and AI systems and applying novel techniques judiciously in production.
• Excellent communication and presentation skills, including the ability to explain complex AI concepts to peers.
• Experience building and leading a multi-team AI organization delivering multiple enterprise products or capabilities concurrently.
• Ability to expand and execute long-term AI platform strategies aligned with enterprise priorities and regulatory frameworks.
• Experience establishing cross-functional operating rhythms and review cadences, such as OKRs, AI governance councils, and quarterly reviews.
• Experience right-sizing models, instance counts, and hardware types to meet requirements such as context length, token inputs, and token outputs.

Responsibilities

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
• Oversee the design, development, testing, deployment, and support of AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Make build-versus-buy decisions across open-source and SaaS AI technologies.
• Invent and introduce foundation model optimization techniques to improve the scalability, cost, latency, and throughput of production AI systems.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.
• Attract and retain AI talent and support team members’ personal and professional development.
• Translate enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline.
• Scale AI engineering practices through shared infrastructure, reusable components, and unified observability and governance frameworks.
• Establish enterprise standards for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness.
• Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligibility for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Director