Senior AI Platform Architect — Agentic (Remote)

Capital One; McLean (VA); Remote; USD 315,000 - 359,000; Full time

Job summary

Capital One is seeking a Sr. Distinguished AI Engineer to build and scale AI systems across the enterprise. You will lead architecture for agent orchestration, RAG pipelines, and multi-tenant policies while mentoring engineers and shaping technical design strategies.

The role emphasizes production-ready GenAI SDKs, secure workflows, and measurable reductions in prototyping timelines, with a focus on responsible AI and high-availability platforms.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or AI with 10+ years in AI/ML development.
• At least 10 years of experience programming in Python, Go, Scala, or Java.
• Strong experience deploying scalable AI/ML solutions and cloud platforms.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products for associates and customers.
• Contribute to the north star platform architecture with API design and agent orchestration.
• Evaluate and blend agentic frameworks to meet enterprise SLAs and enable rapid app adoption.
• Develop end-to-end GenAI SDKs, CLIs, and starter kits to accelerate production timelines.
• Advance trust and safety with guardrails, content filters, and audit APIs.
• Collaborate with architects to optimize orchestration, caching, and cost per token.
• Own Helm charts, operators, and CRDs to scale agents across tenants.

Skills

Python

Go

Scala

Java

AI/ML

Education

Bachelor’s degree in Computer Science, Engineering, or AI

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

Tools

LangChain

CrewAI

Semantic Kernel

AutoGen

Kubernetes

LLMOps

Job description

Capital One is seeking a Sr. Distinguished AI Engineer to build and scale AI systems across the enterprise. You will lead architecture for agent orchestration, RAG pipelines, and multi-tenant policies while mentoring engineers and shaping technical design strategies.

The role emphasizes production-ready GenAI SDKs, secure workflows, and measurable reductions in prototyping timelines, with a focus on responsible AI and high-availability platforms.