Distinguished AI Engineer – Agentic AI Platform

Capital One

Distinguished AI Engineer developing AI-powered products that transform customer interactions at Capital One. Collaborating with cross-functional teams to deliver innovative AI solutions.

Posted 6/24/2026full-timeSan Francisco • California, Massachusetts, New York, Virginia • 🇺🇸 United StatesSeniorLead💰 $269,100 - $335,100 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudFirewallsGoJavaKubernetesPythonScala

About the role

Key responsibilities & impact

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.
Standardize and automate agentic workflows.
Evaluate agentic frameworks such as LangGraph, AutoGen, Semantic Kernel, CrewAI and LlamaIndex and then harden/blend patterns that best meet enterprise SLAs.
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.
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 auto-scale agents to hit tenant SLAs.
Coach and evangelize - host architecture office hours, mentor Staff, Principal and Senior engineers, author technical design documents and blogs, represent Capital One at Tier1 AI conferences to amplify platform vision across internal and external communities.

Requirements

What you’ll need

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, service mesh)
Experience staying abreast of the latest AI research and AI systems and applying novel techniques in production.

Benefits

Comp & perks

Health insurance
Financial benefits
Flexible work arrangements
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonGoScalaJavaAI algorithmsML algorithmsAgentic FrameworksLLMOpsK8sGenAI

Soft Skills

leadershipmentoringcommunicationpresentationcollaborationinfluencing stakeholderscoachinginnovationtechnical writingcross-functional teamwork

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in EngineeringMaster's degree in Computer ScienceMaster's degree in Computer Engineering