Lead AI Platform Engineer - Gen AI & Agents

Capital One; McLean (VA); On-site; USD 230,000 - 262,000; Full time

Benefits offered by this job

Health insurance

Competitive benefits package

Paid time off

Job summary

Capital One is seeking an AI Engineer 5 to join the IFX team, delivering responsible AI systems and scalable ML infrastructure. You will partner with engineers, scientists, PMs, and product managers to build AI-powered products, train foundation models, and optimize ML pipelines for performance and cost.

You should have extensive Python/Java/CUDA experience, cloud deployment know-how, and a passion for advancing AI research into production with responsible governance and explainability.

Qualifications

• Bachelor’s degree plus 6+ years AI/ML experience or Master’s with 4+ years of experience.
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference.
• Leverage Open Source and SaaS AI technologies across a broad stack.
• Invent optimization techniques to improve performance, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap of foundational AI systems.
• Design, implement and optimize multi-model orchestration pipelines and governance.

Skills

Python

Go

Scala

CUDA

Java

AI/ML algorithms

Multi-model systems

Agentic AI

Education

Bachelor's Degree in CS/AI/EE/CE

Master's Degree in CS/AI/EE/CE

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

Capital One is seeking an AI Engineer 5 to join the IFX team, delivering responsible AI systems and scalable ML infrastructure. You will partner with engineers, scientists, PMs, and product managers to build AI-powered products, train foundation models, and optimize ML pipelines for performance and cost.

You should have extensive Python/Java/CUDA experience, cloud deployment know-how, and a passion for advancing AI research into production with responsible governance and explainability.