Senior AI Systems Engineer – LLM & Infra

Capital One National Association; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking an AI Engineer 4 to help build responsible AI systems and scalable AI infrastructure. You will design and deploy AI components, training pipelines, inference engines, and governance mechanisms while partnering with cross-functional teams across software, data, and product.

You will optimize performance and cost, mentor engineers, and contribute to the long-term AI platform roadmap with focus on security, compliance, and reliability for production systems.

Qualifications

• Bachelor's degree with 4+ years developing AI/ML algorithms or technologies
• Master's degree with 2+ years developing AI/ML algorithms or technologies
• Experience programming in Python, Go, Scala, CUDA, or Java (4+ years respective)

Responsibilities

• Design, develop, test, deploy, and support AI software components including training, inference, agents, search, and governance.
• Leverage Open Source and SaaS AI tech such as AWS Ultraclusters, HuggingFace, VectorDBs, and PyTorch.
• Optimize model performance, latency, and cost via foundation model techniques for production systems.
• Own end-to-end architecture for complex AI systems, ensuring maintainability, observability, and ethics alignment.
• Define SLOs for AI reliability, latency, uptime, and drift, collaborating with infra to optimize GPUs/TPUs.

Skills

Python

Go

Scala

CUDA

Java

Distributed systems

Education

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Tools

AWS

HuggingFace

PyTorch

VectorDBs

Open Source AI tools

Job description

Capital One is seeking an AI Engineer 4 to help build responsible AI systems and scalable AI infrastructure. You will design and deploy AI components, training pipelines, inference engines, and governance mechanisms while partnering with cross-functional teams across software, data, and product.

You will optimize performance and cost, mentor engineers, and contribute to the long-term AI platform roadmap with focus on security, compliance, and reliability for production systems.