Senior Gen AI Platform Engineer

Capital One; California; Hybrid; USD 251,000 - 286,000; Full time

Job summary

Capital One Group is seeking an AI Engineer 5 for Gen AI Platform Services focused on agentic systems. You will design, train, and deploy AI software components including LLM inference, agents, and orchestration pipelines within a responsible AI framework.

Leadership and collaboration across researchers, engineers, and PMs are essential. The role emphasizes scalable AI infrastructure, performance optimization, and governance with strong emphasis on ethical deployment and explainability.

Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI/ML algorithms or a Master's with 4+ years.
• Experience with Python, Go, Scala, CUDA, or Java (6+ years).
• Experience deploying scalable AI solutions on cloud platforms (AWS/GC/Azure).
• Experience in LLM inference, vector databases, similarity search, and guardrails.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components.
• Lead foundation model optimization for performance, cost, and latency.
• Architect multi-model orchestration pipelines integrating LLMs and vector searches.

Skills

Python

Go

Scala

CUDA

Java

Education

Bachelor's degree in Computer Science/AI/EE/CE

Master's degree in related field

Tools

AWS

Google Cloud

Azure

Huggingface

VectorDBs

PyTorch

Job description

Capital One Group is seeking an AI Engineer 5 for Gen AI Platform Services focused on agentic systems. You will design, train, and deploy AI software components including LLM inference, agents, and orchestration pipelines within a responsible AI framework.

Leadership and collaboration across researchers, engineers, and PMs are essential. The role emphasizes scalable AI infrastructure, performance optimization, and governance with strong emphasis on ethical deployment and explainability.