Staff AI Engineer – Remote, Build Scalable AI for Banking

Capital One; Trenton (NJ); Remote; USD 245,000 - 279,000; Full time

Job summary

Capital One is seeking a Staff AI Engineer to design and build AI software components and foundation model workflows. This remote-eligible role collaborates with engineers, researchers, and product managers to deliver AI-powered banking experiences at scale.

The ideal candidate has extensive Python/Java/Scala/CUDA experience, strong ML knowledge, and a track record of building production-grade AI systems with a focus on performance, cost, and governance.

Qualifications

• Bachelor's or Master’s degree in a related field with substantial AI/ML experience.
• At least 8 years of experience programming in 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 models and inference.
• Leverage Open Source and SaaS AI tech such as AWS Ultraclusters, Huggingface, PyTorch.
• Optimize foundation model training and inference for performance, cost, and latency.
• Contribute to the long-term roadmap of foundational AI systems at Capital One.
• Set enterprise‑wide AI architecture directions and tooling standards.
• Own model routing, caching, and orchestration for hybrid workloads.
• Champion responsible AI, transparency, reproducibility, and fairness.
• Drive education and best-practice sharing through architecture councils and AI guilds.

Skills

Python

Go

Scala

CUDA

Java

ML algorithms

Education

Bachelor's degree in CS/EE/CE

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

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

LLM Inference

Similarity Search

Guardrails

Memory

CUDA

Job description

Capital One is seeking a Staff AI Engineer to design and build AI software components and foundation model workflows. This remote-eligible role collaborates with engineers, researchers, and product managers to deliver AI-powered banking experiences at scale.

The ideal candidate has extensive Python/Java/Scala/CUDA experience, strong ML knowledge, and a track record of building production-grade AI systems with a focus on performance, cost, and governance.