Lead AI Engineer: LLM & AI Foundations

Capital One; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking a Lead AI Engineer to advance AI foundations and production-ready ML systems. You will partner with engineers, researchers, PMs and product leads to deliver AI-powered products that impact how associates work and how customers interact with Capital One.

The role focuses on foundation model training, LLM inference, guardrails, evaluation, and observability, with emphasis on scalable, responsible AI and cost efficiency across cloud platforms.

Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus 4+ years of AI/ML experience.
• Master's degree plus 2+ years of AI/ML experience in related fields.

Responsibilities

• Partner with cross-functional team of engineers, researchers, PMs, and product managers to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM optimization techniques to improve performance, scalability, cost, latency, throughput.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.

Skills

Python

Go

Scala

Java

Cloud platforms

Education

Bachelor's degree in CS/AI/EE or related (4+ yrs)

Master's degree in CS/AI/EE or related (2+ yrs)

Tools

AWS

Google Cloud

Azure

HuggingFace

PyTorch

VectorDBs

Nemo Guardrails

Job description

Capital One is seeking a Lead AI Engineer to advance AI foundations and production-ready ML systems. You will partner with engineers, researchers, PMs and product leads to deliver AI-powered products that impact how associates work and how customers interact with Capital One.

The role focuses on foundation model training, LLM inference, guardrails, evaluation, and observability, with emphasis on scalable, responsible AI and cost efficiency across cloud platforms.