Sr. Manager, AI Engineer

The Sr. Manager, AI Engineer role at Information Technology Senior Management Forum focuses on building responsible, scalable AI-powered products in partnership with cross-functional teams. This position oversees end-to-end AI software components, spanning foundational model training, LLM inference, search, guardrails, evaluation, experimentation, governance, and observability, while helping shape the technical roadmap for foundational AI systems at Capital One.

Location: San Jose, CA (onsite)

Role Summary

In this position, you will collaborate across engineering, research, and product functions to deliver AI capabilities that change how associates work and how customers interact with Capital One. The role also includes making judgment-driven build-versus-buy decisions across open source and SaaS AI technologies.

Responsibilities

• Partner with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Oversee design, development, testing, deployment, and support for 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 AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more
• Invent and introduce state-of-the-art foundation model optimization techniques to improve 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, support personal and professional development, and foster a culture of learning and staying current with state-of-the-art AI
• Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts
• Operationalize Responsible AI by establishing review gates, documentation and evaluation requirements, and rollout and rollback standards for production AI systems
• Create collaboration interfaces with Research, Data, and Platform teams to accelerate the model lifecycle

Requirements

• 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 a related field plus at least 4 years of experience
• At least 1 year of people leadership experience

Technologies

• AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, AWS, Google Cloud, Azure
• Python, C++, C#, Java, CUDA, Golang

Preferred Qualifications

• 3 years of experience managing and leading an engineering team
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (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, and Memory using Python, C++, C#, Java, CUDA, or Golang
• Experience building agentic AI systems and agentic workflows
• Passion for staying abreast of the latest AI research and applying novel techniques judiciously in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
• Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery
• Familiarity with MLOps and AI observability including evaluation pipelines, drift monitoring, and model or version governance for reliability and compliance
• Track record mentoring engineers or scientists to productize prototypes and meet production SLOs
• Experience right-sizing models, instance counts, and hardware types given requirements such as context length and token inputs or outputs

Compensation and Incentives

Salary (San Jose, CA): USD 250,800 - 286,200 per year

This role is also eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.

Posted Date

9/21/2026

Additional Information

• Expected to accept applications for a minimum of 5 business days
• No agencies please

Accommodation and Recruiting Contact

• For employment opportunity information or application accommodations: contact Capital One Recruiting at 1-800-304-9102 or [email protected]
• For technical support or questions about the recruiting process: [email protected]