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.

You will contribute to the north star platform architecture, continuously publishing and refining living diagrams and canonical APIs that cover agent orchestration, RAG pipelines, prompt libraries and multi-tenant policy enforcement.

A major emphasis is around standardizing and automating agentic workflows : you will evaluate agentic frameworks such LangGraph, AutoGen, Semantic Kernal, CrewAI and LlamaIndex and then harden / blend patterns that best meet enterprise SLAs do that 90% of new apps adopt them.

Developer experience is another cornerstone. You will contribute to crafting an end to end GenAI SDK, CLI and starter kits that let AI engineers spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%.

Trust and safety remain paramount; you will help bring together a vision of central guardrail services - prompt firewalls, content-filter hooks, red team harnesses and audit APIs - consumed by every application to ensure zero Sev4 incidents.

You will collaborate with cross organization architects to drive end to end performance by optimizing orchestration - level batching, retrieval caching, heuristic tuning to achieve reductions in per token spend. You will accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG.

You’ll own central Helm charts, operators and CRDs that auto scale agents to hit tenant SLAs

Finally you will coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs and representing Capital One at Tier1 AI conferences - to amplify platform vision across internal and external communities.

Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing AI and ML algorithms or technologies

At least 8 years of experience programming with Python, Go, Scala, or Java

8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

2+ years of experience supporting Agentic Frameworks (LangChain, CrewAI, Semantic Kernel (Microsoft), or AutoGen)

2+ years of experience with LLMOps (Google Cloud Vertex AI, Amazon SageMaker, Azure Machine Learning)

8+ years of experience designing mission-critical machine learning platforms

2+ years of experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems

Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level

Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

Master's degree in Computer Science, Computer Engineering, or relevant technical field

Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Experience leading GenAI or LLM-Powered application architectures in production

Deep understanding of Responsible AI, data privacy and multi-tenant security patterns

Experience as a Staff-plus or Distinguished IC engineer influencing 50+ engineers and C-suite stakeholders

K8s mastery (multi-region clusters, sericie mesh)

Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production