Remote Senior AI Platform Engineer — Enterprise Analysis

Capital One National Association; San Jose (CA); Remote; USD 170,000 - 230,000; Full time

Job summary

Capital One is building an AI native platform to empower our business community to run AI-assisted analysis across lines of business. You will join the IFX team to design, develop, test, and deploy AI software components, including foundation model training, LLM inference, agents, and multi-agent workflows.

Collaborate with engineers, researchers, PMs, and product managers to set technical direction, ensure responsible AI, and improve performance, latency, and scalability in production systems.

Qualifications

• Bachelor's or Master's degree as specified with extensive AI/ML development experience
• 8+ years of experience programming in Python, Go, Scala, CUDA
• Experience delivering AI-powered products and scalable AI systems

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components including foundation model training and LLM inference
• Leverage Open Source and SaaS AI tech such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
• Invent optimization techniques to improve performance, scalability, cost, latency, throughput
• Set the technical direction for enterprise-wide AI architecture and governance

Skills

Python

Go

Scala

CUDA

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 building an AI native platform to empower our business community to run AI-assisted analysis across lines of business. You will join the IFX team to design, develop, test, and deploy AI software components, including foundation model training, LLM inference, agents, and multi-agent workflows.

Collaborate with engineers, researchers, PMs, and product managers to set technical direction, ensure responsible AI, and improve performance, latency, and scalability in production systems.