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.
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.
Evaluate agentic frameworks such as LangGraph, AutoGen, Semantic Kernel, CrewAI, and LlamaIndex and then harden/blend patterns that best meet enterprise SLAs so that 90% of new apps adopt them.
Contribute to crafting an end-to-end GenAI SDK, CLI, and starter kits that enable AI engineers to spin up secure, observable agentic workflows in under minutes, shrinking prototyping to production timelines by 30%.
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.
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.
Accelerate innovation by incubating proof of concepts and driving RFCs such as hierarchical agent memory, multimodal guardrails, multimodal RAG.
Own central Helm charts, operators, and CRDs that autoscale agents to hit tenant SLAs.
Coach and evangelize - hosting architecture office hours, mentoring Staff, Principal and Senior engineers, authoring technical design documents and blogs, and representing Capital One at Tier 1 AI conferences - to amplify platform vision across internal and external communities.

Requirements

Bachelor's degree in Computer Science, Engineering, or AI plus at least 10 years of experience developing AI and ML algorithms or technologies, or Master's degree plus at least 8 years of experience developing AI and ML algorithms or technologies
At least 10 years of experience programming with Python, Go, Scala, or Java
9 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
K8s mastery (multi-region clusters, service mesh)
Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production.

Benefits

Health insurance
401(k) matching
Performance based incentive compensation including cash bonuses and/or long-term incentives (LTI)
Committed to non-discrimination
Promote a drug-free workplace

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonGoScalaJavaAI algorithmsML algorithmsAgentic FrameworksLLMOpsKubernetesmachine learning platforms

Soft Skills

leadershipmentoringcommunicationpresentationcollaborationinfluencing stakeholderscoachinginnovationproblem-solvingtechnical writing

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in EngineeringBachelor's degree in AIMaster's degree in Computer ScienceMaster's degree in Computer Engineering