Senior Distinguished AI Engineer (Agentic AI Platform)

Responsibilities

• Partner with cross-functional teams of engineers, research scientists, and product managers to deliver AI-powered products.
• Contribute to north star platform architecture, including agent orchestration, RAG pipelines, and multi-tenant policy enforcement.
• Standardize and automate agentic workflows by evaluating and hardening frameworks such as LangGraph, AutoGen, and LlamaIndex.
• Develop end-to-end GenAI SDKs, CLIs, and starter kits to accelerate prototyping to production timelines.
• Build central guardrail services, including prompt firewalls, content-filter hooks, and red team harnesses.
• Optimize orchestration performance through level batching, retrieval caching, and heuristic tuning.
• Own central Helm charts, operators, and CRDs to auto-scale agents to meet tenant SLAs.
• Coach and mentor Staff and Principal engineers while representing Capital One at Tier 1 AI conferences.

Requirements

• Bachelor's degree in Computer Science, Engineering, or AI plus 10 years of experience, or a Master's degree plus 8 years of experience.
• At least 10 years of professional programming experience in Python, Go, Scala, or Java.
• Proven experience with Agentic Frameworks (e.g., LangChain, CrewAI, AutoGen, or Semantic Kernel).
• Experience with LLMOps (e.g., Vertex AI, SageMaker, or Azure Machine Learning).
• Mastery of Kubernetes (K8s), including multi-region clusters and service mesh.

Preferred Qualifications

• 9+ years of experience deploying scalable AI solutions on cloud platforms like AWS, GCP, or Azure.
• 8+ years of experience designing mission-critical machine learning platforms.
• Deep understanding of Responsible AI, data privacy, and multi-tenant security patterns.
• Experience optimizing training and inference software for hardware utilization, latency, and throughput.
• Demonstrated ability to lead multiple engineering teams and influence stakeholders up to the VP level.

About the Company

Capital One is an industry leader in using machine learning to create real-time, personalized customer experiences. We are committed to building world-class applied science and engineering teams to deliver breakthrough product experiences and scalable, high-performance AI infrastructure.