Team Description

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers.  Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

About the Team 

This team owns the infrastructure layer between applications and foundation models: model access, routing, reliability, security integration, observability, and cost management behind a single governed interface. Product teams build on the platform instead of integrating with model providers directly, which means the enterprise adopts new model capability once, centrally, rather than many times over. Sitting in the request path for every AI-powered application makes latency, reliability, and efficiency company-level outcomes rather than local ones.

This team also owns a measurement and attribution layer that makes consumption legible to the optimization capabilities that act on it, including intelligent routing, caching, context optimization, and capacity planning. The objective is cost per unit of business outcome, not spend reduction in isolation. The architecture set now will determine the enterprise's cost curve and build velocity for years, and this role owns both those decisions and the teams that execute them.

In this role, you will: 

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One

• Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

• Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more

• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems

• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One

• Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI

The Ideal Candidate:

• You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good

• Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production

• You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example

• You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven

• You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss

• You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown

Basic Qualifications:

• Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing or leading 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 (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

• Master's degree in Computer Science, Computer Engineering, or relevant technical field

• Passion for staying up to date with the latest AI research and AI systems, and judiciously apply novel techniques in production

• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.