Senior AI Engineer, Enterprise Analysis Platform (Remote)

Military Friendly Company; Indianapolis (IN); Remote; USD 245,000 - 279,000; Full time

Job summary

Capital One is seeking a Staff AI Engineer to join the Enterprise Analysis Platform, focused on building an AI-native, scalable analytics platform for thousands of users. You will work across foundation models, inference, agents, and observability to deliver enterprise AI capabilities.

Ideal candidates will lead multi-disciplinary teams, apply the latest AI research in production, and drive architecture standards for governance, observability, and cost efficiency.

Qualifications

• Bachelor's or Master’s in a technical field with extensive AI/ML algorithm experience.
• 8+ years coding with Python, Go, Scala, CUDA, or Java.
• Experience designing and deploying AI systems in production environments.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components.
• Leverage Open Source and SaaS AI tech like AWS Ultraclusters, HuggingFace, and PyTorch.
• Optimize foundation model training and inference for performance and cost.
• Contribute to the technical vision and long-term AI platform roadmap.
• Set enterprise-wide AI architecture direction and standards.
• Own model routing, caching, and orchestration for mixed workloads.
• Champion responsible AI practices including transparency and fairness.

Skills

Python

Go

Scala

CUDA

Java

AI systems

Distributed systems

Education

Bachelor's in CS/AI/EE

Master's in CS/AI/EE

Tools

AWS

HuggingFace

PyTorch

VectorDBs

Job description

Capital One is seeking a Staff AI Engineer to join the Enterprise Analysis Platform, focused on building an AI-native, scalable analytics platform for thousands of users. You will work across foundation models, inference, agents, and observability to deliver enterprise AI capabilities.

Ideal candidates will lead multi-disciplinary teams, apply the latest AI research in production, and drive architecture standards for governance, observability, and cost efficiency.