Capital One’s Intelligent Foundations and Experiences (IFX) team is building and deploying proprietary AI solutions that power high-impact products for millions of customers. As a Director AI Engineer in this onsite role in San Jose, CA, you will help advance foundational AI capabilities and deliver responsible, reliable AI-powered experiences across the enterprise.
This position blends technical leadership with execution: you will oversee AI software components from training and inference to evaluation, guardrails, experimentation, and observability. You will also make high-judgment build-versus-buy decisions across a modern stack of open source and SaaS technologies, while translating enterprise AI strategy into portfolio-level plans.
Responsibilities
- Partner with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how associates work and how customers interact with Capital One.
- Oversee the end-to-end 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.
- Make high judgment build-versus-buy decisions across a broad stack of open source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
- Introduce state-of-the-art foundation model optimization techniques to improve performance across scalability, cost, latency, and throughput for large-scale production AI systems.
- Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
- Attract and retain top AI talent, nurture team development, and foster a culture of learning and staying current with state-of-the-art in AI.
- Translate enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline.
- Scale AI engineering practices using 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 support alignment with emerging ethical and regulatory standards for deployed systems.
Requirements
- Bachelor’s or Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields, plus experience developing AI and ML algorithms or technologies (8+ years with a Bachelor’s, or 6+ years with a Master’s).
- 3+ years of people leadership experience.
- Strong interest in staying abreast of the latest research and the ability to understand scientific publications and apply novel techniques in production.
- Fulfillment in empowering others through mentoring and coaching, and willingness to be hands-on when necessary while leading by example.
- Ability to bring clarity to large, undefined problems, ask deep questions to identify root causes, and communicate findings concisely.
- Deep technical expertise with a strong foundation in engineering and mathematics, plus experience across hardware, software, and AI optimization.
- Resilience and the ability to forge new paths to achieve business goals when the route is unknown.
Preferred Qualifications
- 5+ years of experience managing and leading an engineering team.
- 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience developing AI/ML algorithms or technologies such as LLM Inference, Similarity Search and VectorDBs, Guardrails, and Memory using Python, C++, C#, Java, CUDA, or Golang.
- Experience building agentic AI systems and agentic workflows.
- Excellent communication and presentation skills for articulating complex AI concepts to peers.
- Experience building and leading multi-team AI organizations delivering multiple enterprise products or capabilities concurrently.
- Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks.
- Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews).
- Experience right-sizing models, instance counts, and hardware types based on requirements such as context length and token inputs/outputs.
Technologies
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, C++, C#, Java, CUDA, Golang, foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, observability, memory, agentic AI systems, agentic workflows.
Compensation and Benefits
Salary range: USD 293,600 - 335,100 per year (San Jose, CA). Performance based incentive compensation may be available, which may include cash bonus(es) and/or long term incentives (LTI).
Capital One offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits to support your total well-being.
Team Overview
The IFX team brings Capital One’s AI vision to life by partnering across the company to advance science and AI engineering, and by building and deploying proprietary solutions central to the business. Their models and platforms help teams across Capital One enhance products with transformative AI in responsible and scalable ways.
Location and Notes
Location: San Jose, CA (onsite).
This role is expected to accept applications for a minimum of 5 business days. No agencies please.
If you need an accommodation related to employment opportunities or applying for a position, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. For technical support or questions about the recruiting process, email Careers@capitalone.com.
