Sr. Manager, AI Engineer
About The Position
Capital One is hiring a Sr. Manager, AI Engineer to help build responsible, reliable, and scalable AI systems and products. The role is part of the Intelligent Foundations and Experiences (IFX) team, which develops proprietary AI models and platforms for use across the company and works with partners to advance AI science and engineering. The position partners with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products. It oversees AI software components across the lifecycle, makes build-versus-buy decisions across open-source and SaaS technologies, and develops optimization techniques for large-scale production AI systems. The role contributes to the technical vision and roadmap for foundational AI systems, translates enterprise goals into measurable team plans, and operationalizes Responsible AI standards. The Sr. Manager attracts and develops talent, mentors team members, and creates strong collaboration with Research, Data, and Platform teams. This is a hybrid position subject to Capital One’s hybrid policy and required on-site presence at the designated office location.
Requirements
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, and at least 6 years of experience developing AI and ML algorithms or technologies; or a master’s degree in one of these fields and at least 4 years of such experience.
- At least 1 year of people leadership experience.
- Strong foundation in engineering and mathematics, with expertise in hardware, software, and AI.
- Ability to understand scientific publications and apply novel techniques in production.
- Ability to lead by example, mentor and coach others, and support professional development.
- Ability to adapt quickly, clarify undefined problems, investigate root causes, and communicate findings clearly.
- Excellent communication and presentation skills, including the ability to explain complex AI concepts to peers.
Nice To Haves
- At least 3 years of experience managing and leading an engineering team.
- At least 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 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.
- Experience leading technical strategy for a multidisciplinary AI team, 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.
- Passion for following the latest AI research and systems and applying novel techniques judiciously in production.
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.
- Develop foundation model optimization techniques to improve scalability, cost, latency, and throughput of 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 team members’ personal and professional development.
- Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts.
- Establish Responsible AI 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.
- Lead technical strategy for a multidisciplinary AI team while balancing research exploration with production delivery.
- Mentor and coach engineers and scientists, helping productize prototypes and meet production SLOs.
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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
