Senior AI Engineer, Gen AI Platform & Agentic AI

Capital One; United States; Remote; USD 197,000 - 246,000; Full time

Job summary

Capital One is seeking an AI Engineer 4 to help build responsible and scalable AI systems across our Gen AI platform, collaborating with engineers, researchers, PMs, and product managers to deliver AI-powered financial services that improve customer experiences in real time.

The role covers foundation model training, inference, agents and workflows, and observability, with a broad stack including AWS, Hugging Face, VectorDBs, and PyTorch.

Qualifications

• Bachelor's degree required in CS/EE/CE or related field.
• Master's degree plus 2+ years of AI/ML development experience.
• At least 4 years of experience programming languages listed.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve performance, scalability, cost, latency, throughput.

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

Python

Go

Scala

CUDA

Java

C++

C#

Golang

Job description

Capital One is seeking an AI Engineer 4 to help build responsible and scalable AI systems across our Gen AI platform, collaborating with engineers, researchers, PMs, and product managers to deliver AI-powered financial services that improve customer experiences in real time.

The role covers foundation model training, inference, agents and workflows, and observability, with a broad stack including AWS, Hugging Face, VectorDBs, and PyTorch.