Senior AI Engineer: Foundation Models & Scalable AI

Capital One; San Jose (CA); On-site; USD 251,000 - 286,000; Full time

Job summary

Capital One is seeking an AI Engineer 5 to join the Intelligent Foundations and Experiences (IFX) team, building responsible AI systems and scalable infrastructure that power real-time customer experiences.

You will collaborate with engineers, researchers, PMs, and product teams to design, develop, deploy, and optimize AI components, including foundation models, LLM inference, and multi-model pipelines, with a focus on cost-performance and governance.

Qualifications

• Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of AI/ML experience, or a Master's degree plus at least 4 years.
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java

Responsibilities

• Partner with cross-functional 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, agents, and multi-model workflows.
• Leverage Open Source and SaaS AI technologies such as AWS, Huggingface, PyTorch, and VectorDBs.
• Invent and introduce foundation model optimization techniques to improve performance, cost, and latency.
• Lead governance and visualization tasks ensuring AI systems meet standards and cost controls.

Skills

Python

Go

Scala

CUDA

Java

AI/ML

Education

Bachelor's or Master's in Computer Science/AI/EE/CE

6+ years with Bachelor's or 4+ years with Master's in AI/ML

Tools

Huggingface

PyTorch

AWS

VectorDBs

Job description

Capital One is seeking an AI Engineer 5 to join the Intelligent Foundations and Experiences (IFX) team, building responsible AI systems and scalable infrastructure that power real-time customer experiences.

You will collaborate with engineers, researchers, PMs, and product teams to design, develop, deploy, and optimize AI components, including foundation models, LLM inference, and multi-model pipelines, with a focus on cost-performance and governance.