AI Engineer (Remote Eligible)

# Director, AI Engineer (Remote Eligible)

## About the Role

Capital One is building responsible, reliable, and scalable AI systems to transform banking and customer experiences. As a Director, AI Engineer on the Intelligent Foundations and Experiences (IFX) team, you will lead the development and delivery of foundational AI capabilities that support products and business functions across Capital One.

You will work with engineers, research scientists, technical program managers, product managers, compliance, and enterprise risk teams to advance AI engineering, foundation models, large language models, agentic systems, responsible AI, and production-scale AI infrastructure. This role combines deep technical leadership, organizational leadership, enterprise AI strategy, and hands-on engagement with emerging AI technologies.

**Capital One is open to hiring a Remote Employee for this opportunity.**

## Key Responsibilities

* Partner with cross-functional engineering, research, product, and program teams to deliver AI-powered products and capabilities.

* Oversee the design, development, testing, deployment, and support of AI software components, including:

* Foundation model training

* Large language model inference

* Similarity search and VectorDBs

* Guardrails

* Model evaluation and experimentation

* AI governance

* Observability

* Make build-vs-buy decisions across open-source and SaaS AI technologies, including AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch.

* Develop and introduce foundation model optimization techniques to improve scalability, cost, latency, throughput, and overall production performance.

* Contribute to the technical vision and long-term roadmap for foundational AI systems.

* Translate enterprise AI strategy into portfolio-level execution plans across multiple product areas.

* Scale AI engineering practices through shared infrastructure, reusable components, observability, and governance frameworks.

* Establish enterprise standards for Responsible AI, including fairness metrics, model evaluation protocols, documentation, and audit readiness.

* Partner with research, compliance, and enterprise risk teams to ensure AI systems meet ethical and regulatory standards.

* Build, lead, attract, and retain high-performing AI engineering talent.

* Mentor and coach team members and foster a culture of continuous learning and technical development.

* Stay current with AI research and apply novel techniques appropriately to production systems.

* Balance innovation with delivery discipline while providing technical direction on complex and ambiguous problems.

## Required Qualifications

* Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field **plus at least 8 years of experience** developing AI and ML algorithms or technologies; **or**

* Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field **plus at least 6 years of experience** developing AI and ML algorithms or technologies.

* At least 3 years of people leadership experience.

## Preferred Qualifications

* 5+ years of experience managing and leading an engineering team.

* 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.

* Experience developing AI and ML technologies such as LLM inference, similarity search, VectorDBs, guardrails, and memory.

* Programming experience with Python, C++, C#, Java, CUDA, or Golang.

* Experience building agentic AI systems and agentic workflows.

* Experience applying current AI research and novel techniques to production systems.

* Excellent communication and presentation skills, including the ability to explain complex AI concepts clearly.

* Experience building and leading multi-team AI organizations delivering multiple enterprise products or capabilities concurrently.

* Proven ability to develop and execute long-term AI platform strategies aligned with enterprise priorities and regulatory frameworks.

* Experience establishing cross-functional operating rhythms and review cadences, including OKRs, AI governance councils, and quarterly reviews.

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