Senior AI Platform Engineer: Foundation Models & Agents

Capital One; United States; Remote; USD 230,000 - 286,000; Full time

Benefits offered by this job

Performance based incentives

Job summary

Capital One is building responsible and reliable AI systems to transform banking experiences for customers and partners. The AI Engineer 5 will work in the IFX team to advance AI foundations, deploy AI-powered products, and optimize large-scale production AI systems.

You will collaborate with engineers, scientists, and product managers to push the boundaries of AI in a financial services context. The role emphasizes scalable architecture, governance, and cost-performance optimization while

Qualifications

• Bachelor's degree in CS/AI/EE/CE or related field with 6+ years AI/ML experience, or Master’s with 4+ years.
• 6+ years programming in Python, Go, Scala, CUDA, or Java.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products for associates and customers.
• Design, develop, test, deploy, and support AI software including foundation model training and LLM inference.
• Implement and optimize multi-model orchestration pipelines with LLMs, vector search, and domain models.
• Lead governance reviews for GPU utilization, model throughput, and inference cost efficiency.
• Mentor Senior engineers and drive technical maturity across teams.

Skills

Python

Go

Scala

CUDA

Java

Education

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

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

Capital One is building responsible and reliable AI systems to transform banking experiences for customers and partners. The AI Engineer 5 will work in the IFX team to advance AI foundations, deploy AI-powered products, and optimize large-scale production AI systems.

You will collaborate with engineers, scientists, and product managers to push the boundaries of AI in a financial services context. The role emphasizes scalable architecture, governance, and cost-performance optimization while