Senior AI Systems Engineer – Foundation Models

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

Job summary

Capital One is seeking an AI Engineer 5 (MLXT) to build responsible and scalable AI systems. You will partner with engineers, researchers, PMs, and product managers to deploy AI-powered products across banking experiences.

The role involves foundation model training, LLM inference, multi-agent workflows, and optimization across GPU-powered pipelines, with a focus on cost, latency, and scalability. You will mentor engineers and contribute to Capital One's AI roadmap.

Qualifications

• Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java

Responsibilities

• Partner with cross-functional team to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components
• Leverage a broad stack of Open Source and SaaS AI technologies
• Invent and introduce foundation model optimization techniques to improve performance
• Contribute to the technical vision and long-term roadmap of foundational AI systems
• Design, implement and optimize multi-model orchestration pipelines
• Establish and lead cost-performance governance reviews across AI systems
• Mentor Principal and Manager-level AI engineers

Skills

Python

Go

Scala

CUDA

Java

Cloud platforms

HuggingFace

VectorDBs

PyTorch

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 Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

Capital One is seeking an AI Engineer 5 (MLXT) to build responsible and scalable AI systems. You will partner with engineers, researchers, PMs, and product managers to deploy AI-powered products across banking experiences.

The role involves foundation model training, LLM inference, multi-agent workflows, and optimization across GPU-powered pipelines, with a focus on cost, latency, and scalability. You will mentor engineers and contribute to Capital One's AI roadmap.