Senior AI Engineer: Foundation Models & Scalable AI

Capital One; San Francisco (CA); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking an AI Engineer to partner with a cross-functional team to deliver AI-powered products and services that transform how associates work and how customers interact with the bank.

You will design, develop, and deploy AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, and similarity search, while ensuring governance, observability, and scalable performance.

Qualifications

• Bachelor's or Master’s in a technical field with practical AI/ML implementation experience.
• Proficient in Python and at least one of Go/Scala/CUDA/Java.
• Experience shipping production AI/ML systems.
• Strong fundamentals in engineering, math, and systems design.

Responsibilities

• Deliver AI-powered products with cross-functional teams (engineers, researchers, PMs).
• Design, develop, test, deploy, and support AI software components (foundation model training, LLM inference, agents, search, guardrails).
• Optimize performance, latency, cost, and observability for large-scale AI systems.
• Define and meet SLOs for AI reliability; collaborate on GPU/TPU utilization and inference pipelines.
• Lead technical reviews and mentor senior associates on scalable design and production translation.

Skills

Python

Go

Scala

CUDA

Java

Education

Bachelor's degree in Computer Science/AI/EE/CE or related, plus 4+ years experience

Master's degree in Computer Science/AI/EE/CE or related, plus 2+ years experience

Tools

PyTorch

Hugging Face

VectorDBs

AWS

Job description

Capital One is seeking an AI Engineer to partner with a cross-functional team to deliver AI-powered products and services that transform how associates work and how customers interact with the bank.

You will design, develop, and deploy AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, and similarity search, while ensuring governance, observability, and scalable performance.