Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)

Capital One • San Francisco, NY

2d

About The Position

Capital One’s Intelligent Foundations and Experiences (IFX) team builds and deploys proprietary AI solutions that support products across the company and deliver value to millions of customers. The team works with partners across Capital One to advance AI science and engineering and to deploy AI capabilities responsibly and at scale.

The Sr. Manager, AI Engineer leads work on foundational AI platform services, including agentic AI, guardrails, and evaluation. The role partners with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers. It oversees the design, development, testing, deployment, and support of AI software components, and contributes to the technical vision and long-term roadmap for foundational AI systems.

This position combines hands-on technical leadership with people management. It involves making build-versus-buy decisions across open-source and SaaS AI technologies, developing optimization techniques for production AI systems, translating enterprise goals into team roadmaps, and operationalizing responsible AI practices. The role also develops talent, fosters learning, and builds strong collaboration with Research, Data, and Platform teams.

Requirements

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, plus at least 6 years of experience developing AI and ML algorithms or technologies; or a master’s degree in one of these fields plus at least 4 years of such experience.
• At least 1 year of people leadership experience.

Nice To Haves

• 3 years of experience managing and leading an engineering team.
• 6 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 vector databases, guardrails, or memory, using Python, C++, C#, Java, CUDA, or Golang.
• Experience building agentic AI systems and agentic workflows.
• Passion for following AI research and systems developments and applying novel techniques in production.
• Excellent communication and presentation skills, including the ability to explain complex AI concepts to peers.
• Experience leading technical strategy for a multidisciplinary AI team while balancing research exploration with production delivery.
• Familiarity with MLOps and AI observability, including evaluation pipelines, drift monitoring, and model/version governance.
• Track record of mentoring engineers or scientists to productize prototypes and meet production SLOs.
• 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 for associates and customers.
• 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 scalability, cost, latency, and throughput in large-scale production AI systems.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• Attract and retain AI talent and support the personal and professional development of the team.
• Foster a culture of learning and staying current with advances in 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 production rollout and rollback standards.
• Create collaboration interfaces with Research, Data, and Platform teams to accelerate the model lifecycle.

Benefits

• Comprehensive 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: Senior