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

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real‑time, personalized customer experiences. Our investments in technology infrastructure and world‑class talent—along with our deep experience in machine learning—position us to be at the forefront of enterprises leveraging AI.

Team Description

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand‑in‑hand with partners across the company to advance the state of the art in science and AI engineering, building and deploying proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

Responsibilities

• Partner with a cross‑functional team of engineers, research scientists, technical program managers, and product managers to deliver AI‑powered products that change how our associates work and how our customers interact with Capital One.
• Oversee 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.
• Make high‑judgment build‑vs‑buy decisions across a broad stack of open‑source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, PyTorch, and more.
• Invent and introduce state‑of‑the‑art foundation model optimization techniques to improve performance—scalability, cost, latency, throughput—of large‑scale production AI systems.
• Contribute to the technical vision and long‑term roadmap of foundational AI systems at Capital One.
• Attract and retain top talent in the AI industry and nurture personal and professional development for your team.
• Foster a culture of learning and staying abreast of the state‑of‑the‑art in AI.
• Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts.
• Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems.
• Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate the model lifecycle.

Ideal Candidate

• You love to build systems, take pride in the quality of your work, and share our passion to do the right thing, aiming to change banking for good.
• Passionate about staying abreast of the latest research, with the ability to intuitively understand scientific publications and judiciously apply novel techniques in production.
• Find fulfillment in empowering others, actively driving professional development through mentoring and coaching.
• Hands‑on when necessary and lead by example.
• Adapt quickly, thrive on bringing clarity to big, undefined problems, and articulate findings concisely.
• Have the courage to share new ideas even when they are unproven.
• Deeply technical, with a strong foundation in engineering and mathematics, and expertise in hardware, software, and AI that enables you to spot optimization opportunities others miss.
• Resilient trailblazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field plus at least 6 years of experience developing AI/ML algorithms or technologies, **or** a Master’s degree in one of those fields plus at least 4 years of relevant experience.
• At least 1 year of people‑leadership experience.

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 (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience developing AI/ML algorithms or technologies (e.g., LLM inference, similarity search and VectorDBs, guardrails, memory) using Python, C++, C#, Java, CUDA, or Go.
• Experience building agentic AI systems and agentic workflows.
• Passion for staying abreast of the latest AI research and applying novel techniques 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 (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance.
• Track record mentoring engineers/scientists to productize prototypes and meet production SLOs.
• Experience right‑sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs).

Pay

• Cambridge, MA: $229,900 – $262,400
• McLean, VA: $229,900 – $262,400
• New York, NY: $250,800 – $286,200
• San Francisco, CA: $250,800 – $286,200
• San Jose, CA: $250,800