Director of AI Engineering — Remote

Capital One; Springfield (IL); Remote; USD 245,000 - 279,000; Full time

Job summary

Capital One is seeking a Director, AI Engineer to lead AI initiatives across the enterprise. This role focuses on building responsible and scalable AI systems, leading a multi-disciplinary team of engineers, researchers, and product managers, and making strategic build-vs-buy decisions.

Remote eligibility is offered, with location-flexible support for talented leaders who can drive impact at scale. The ideal candidate will oversee model training, inference, evaluation, governance, and

Qualifications

• Bachelor's or Master's in a related field with requisite AI/ML experience.
• At least 3 years of people leadership experience.
• Experience deploying scalable and responsible AI solutions on cloud platforms.

Responsibilities

• Lead cross-functional teams to deliver AI-powered products and capabilities.
• Oversee design, development, testing, deployment, and support of AI software components.
• Make build-vs-buy decisions across Open Source and SaaS AI technologies.
• Innovate foundation model optimization for performance, cost, and latency.
• Contribute to long-term AI platform vision and roadmaps.
• Mentor and develop AI engineers, fostering a learning culture.
• Translate enterprise AI strategy into portfolio execution plans.
• Scale AI engineering practices with shared infrastructure and governance.

Skills

Leadership

AI engineering

Cross-functional collaboration

Cloud platforms

Education

Bachelor's in CS/EE/CE

Master's in CS/AI/EE

Tools

AWS

Google Cloud

Azure

PyTorch

HuggingFace

VectorDBs

Python

C++

CUDA

Job description

Capital One is seeking a Director, AI Engineer to lead AI initiatives across the enterprise. This role focuses on building responsible and scalable AI systems, leading a multi-disciplinary team of engineers, researchers, and product managers, and making strategic build-vs-buy decisions.

Remote eligibility is offered, with location-flexible support for talented leaders who can drive impact at scale. The ideal candidate will oversee model training, inference, evaluation, governance, and