Capital One is seeking a Senior Lead AI Engineer focused on AI Foundations to design, build, and deploy core AI software components while leading cross-functional teams. This on-site role in McLean, Virginia, emphasizes governance, observability, and performance optimization for foundational AI systems, shaping the long-term technical direction of the company’s AI initiatives.
Location: McLean, VA (onsite) · Salary: USD 229,900 - 262,400 per year
Overview
The role centers on delivering robust AI foundations, contributing to the design and deployment of foundational AI capabilities, and guiding a team toward scalable, reliable, and observable AI systems. The position advances Capital One's technical vision for AI foundations and works to ensure governance and efficiency across AI/ML deployments.
Team Description
The Intelligent Foundations and Experiences (IFX) team sits at the heart of Capital One’s AI strategy. It collaborates with partners across the organization to push the frontiers of AI engineering and science, building proprietary solutions that scale to millions of customers and empower product teams to infuse AI into their offerings.
In This Role
- Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI powered products that transform how associates work and how customers interact with Capital One.
- Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Utilize a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
- Invent and apply advanced LLM optimization techniques to improve scalability, cost, latency, and throughput for large-scale production AI systems.
- Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.
The Ideal Candidate
- You love building systems, take pride in quality work, and share the goal of improving banking for good.
- You stay current with the latest research and can translate publications into practical, production-ready techniques.
- You adapt quickly, bring clarity to complex problems, ask insightful questions, and communicate findings succinctly. You also share new ideas when appropriate, even if unproven.
- You are deeply technical, with a strong foundation in engineering and mathematics, and you recognize optimization opportunities across hardware, software, and AI.
- You are a resilient trailblazer who can forge new paths to meet business goals when the route is unclear.
Basic Qualifications
- Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field with at least 6 years of AI/ML algorithm development experience, or a Master's degree in the same fields with at least 4 years of AI/ML experience.
- At least 6 years of programming experience in Python, Go, Scala, or Java.
Preferred Qualifications
- 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience designing, developing, integrating, delivering, and supporting complex AI systems.
- Proven ability to lead and mentor an engineering team and influence cross-functional stakeholders.
- Experience developing AI/ML algorithms or technologies (e.g., LLM inference, similarity search and VectorDBs, guardrails, memory) using Python, C++, C#, Java, or Golang.
- Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
- Strong commitment to staying current with AI research and systems, with the ability to judiciously apply novel techniques in production.
- Excellent communication and presentation skills, capable of articulating complex AI concepts to peers.
Technologies
- AWS Ultraclusters
- Huggingface
- VectorDBs
- Nemo Guardrails
- PyTorch
- Python
- Go
- Scala
- Java
Benefits
- Health, financial and other benefits that support total well-being
- Performance-based incentive compensation (cash bonuses and/or long-term incentives), discretionary or non-discretionary depending on the plan
