Director AI Engineer

Capital One • San Jose, CA

21h

About The Position

Capital One is hiring a Director AI Engineer for its Intelligent Foundations and Experiences (IFX) team, which develops proprietary AI models and platforms to support products across the company and serve millions of customers. The role partners with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products and scalable AI infrastructure.

The Director oversees the design, development, testing, deployment, and support of AI software components, including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability. The role makes build-versus-buy decisions across open-source and SaaS technologies, develops foundation-model optimization techniques, and contributes to the technical vision and long-term roadmap for Capital One’s foundational AI systems.

This leader translates enterprise AI strategy into execution across product areas, scales engineering practices through shared infrastructure and reusable components, and establishes responsible AI standards. The role also builds and develops teams, supports collaboration with research, compliance, and enterprise risk partners, and helps ensure deployed systems meet ethical and regulatory standards.

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 these fields and at least 6 years of such experience.
• At least 3 years of people leadership experience.
• Strong foundation in engineering and mathematics, with expertise in hardware, software, and AI.
• Ability to understand scientific publications and apply relevant techniques in production.
• Ability to mentor and coach others and drive professional development.
• Ability to clarify and solve large, undefined problems, investigate root causes, and communicate findings clearly.
• Ability to lead by example and be hands-on when necessary.
• Resilience and ability to forge new paths to achieve business goals.

Nice To Haves

• 5+ years of experience managing and leading an engineering team.
• 7+ 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, VectorDBs, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Golang.
• Experience building agentic AI systems and workflows.
• 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.
• Proven 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 based on requirements such as context length and token inputs and 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, evaluation, experimentation, governance, and observability.
• Make build-versus-buy decisions across open-source and SaaS AI technologies.
• Develop and introduce foundation-model optimization techniques to improve production-system scalability, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap for foundational AI systems.
• Attract and retain AI talent and support team members’ personal and professional development through leadership, mentoring, and coaching.
• Foster a culture of learning and staying current with developments in AI.
• Translate enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline.
• Scale AI engineering practices across teams 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.
• Build and lead multi-team AI organizations delivering multiple enterprise products or capabilities concurrently.
• Establish cross-functional operating rhythms and review cadences, such as OKRs, AI governance councils, and quarterly reviews.
• Right-size models, instance counts, and hardware types to meet requirements such as context length and token inputs and outputs.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.
• Eligible 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