Staff AI Engineer — Remote, Scalable AI Systems

Capital One Group; Olympia (WA); Remote; USD 245,000 - 279,000; Full time

Benefits offered by this job

Remote work eligibility

Competitive compensation

Benefits package

Job summary

Capital One is hiring a Staff AI Engineer (Remote Eligible) to help build responsible and reliable AI systems for banking. You will collaborate with engineers, researchers, PMs, and product managers to deliver AI-powered products and scalable infrastructure.

You’ll work with a broad stack including AWS, Huggingface, VectorDBs, and PyTorch, and drive optimization for performance, cost, latency, and throughput while upholding responsible AI practices across the platform.

Qualifications

• Bachelor's or Master's in CS/AI/EE/CE with 6–8+ years in AI/ML development.
• 8+ years Python/Go/Scala/CUDA/Java programming experience.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components.
• Leverage Open Source and SaaS AI technologies (AWS, Huggingface, VectorDBs, PyTorch).
• Invent optimization techniques for foundation models to improve performance, cost, latency, and throughput.
• Contribute to the technical vision and roadmap for foundational AI systems at Capital One.
• Set enterprise-wide AI architecture direction and standards.
• Own model routing, caching, and orchestration for hybrid/multi-model workloads.
• Champion responsible AI with transparency and fairness-by-design.

Skills

Python

Go

Scala

CUDA

Java

LLM Inference

VectorDBs

PyTorch

Guardrails

Observability

Education

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

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

Tools

AWS

Google Cloud

Azure

Job description

Capital One is hiring a Staff AI Engineer (Remote Eligible) to help build responsible and reliable AI systems for banking. You will collaborate with engineers, researchers, PMs, and product managers to deliver AI-powered products and scalable infrastructure.

You’ll work with a broad stack including AWS, Huggingface, VectorDBs, and PyTorch, and drive optimization for performance, cost, latency, and throughput while upholding responsible AI practices across the platform.