Capital One is seeking a Director AI Engineer to help develop responsible and reliable AI systems and foundational AI capabilities through the Intelligent Foundations and Experiences (IFX) team. The role will lead AI software components end-to-end while translating enterprise AI strategy into portfolio execution.

Team Overview

The Intelligent Foundations and Experiences (IFX) team sits at the center of delivering Capital One’s AI vision. The team partners across the organization to advance state-of-the-art science and AI engineering, and it builds and deploys proprietary solutions that support core business needs and value millions of customers. AI models and platforms from IFX enable teams across Capital One to enhance products with responsible and scalable AI.

Responsibilities

Partner with cross-functional leaders across engineering, research science, technical program management, and product to deliver AI-powered products for how associates work and how customers interact with Capital One.
Oversee the design, development, testing, deployment, and support of AI software components, including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Make high judgment build-versus-buy decisions across a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
Develop and introduce state-of-the-art foundation model optimization techniques to improve performance across scalability, cost, latency, and throughput for large scale production AI systems.
Contribute to technical vision and long term roadmap planning for foundational AI systems.
Attract and retain AI engineering talent and support personal and professional development through mentorship, coaching, and a culture focused on continuous learning and keeping pace with advances in AI.
Translate enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline.
Scale AI engineering practices across teams using shared infrastructure, reusable components, and unified observability and governance frameworks.
Establish enterprise standards for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness.
Collaborate with research, compliance, and enterprise risk teams to support deployment of systems that meet emerging ethical and regulatory standards.

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 a Master’s degree in 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.
Strong interest in staying current with the latest research, with the ability to interpret scientific publications and apply novel techniques in production.
Motivation to enable others through mentoring and coaching, with hands-on involvement when needed and leading by example.
Ability to bring clarity to large, undefined problems, including deep problem discovery, concise communication of findings, and willingness to share new ideas that may not yet be proven.
Deep technical expertise with a strong foundation in engineering and mathematics, including the ability to recognize and exploit optimization opportunities across hardware, software, and AI.
Resilience and capability to forge new paths when the route to business goals is not fully defined.

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 (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search and VectorDBs, guardrails, memory) using Python, C++, C#, Java, CUDA, or Golang.
Experience building agentic AI systems and agentic workflows.
Excellent communication and presentation skills, including the ability to articulate complex AI concepts to peers.
Experience building and leading multi-team AI organizations delivering multiple enterprise products or capabilities concurrently.
Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks.
Experience establishing cross-functional operating rhythms and review cadences, such as OKRs, AI governance councils, and quarterly reviews.
Experience right-sizing models, instance counts, and hardware types based on requirements such as context length and token inputs/outputs.

Technologies

AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
Python, C++, C#, Java, CUDA, Golang
Foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, observability, memory
Agentic AI systems, agentic workflows

Compensation and Location

Location: San Jose, CA (onsite).

Base salary range: USD 293,600 - 335,100 per year.

Additional location salary ranges (Director, AI Engineer): Cambridge, MA ($269,100 - $307,200), McLean, VA ($269,100 - $307,200), New York, NY ($293,600 - $335,100), San Francisco, CA ($293,600 - $335,100).

Benefits

Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
Comprehensive, competitive, and inclusive health, financial, and other benefits supporting overall well-being.

Application Details

Posted date: 10/27/2026.

This role is expected to accept applications for a minimum of 5 business days.

No agencies please.

Accommodation and Recruiting Contact

If you require an accommodation to apply for employment opportunities, contact Capital One Recruiting at 1-800-304-9102 or email [email protected].

For technical support or questions about Capital One’s recruiting process, email [email protected].

Director AI Engineer

Job Description