Lead AI Engineer (AI Foundations)

Build foundational AI capabilities that help deliver responsible, reliable experiences for customers and associates at Capital One. This onsite Lead AI Engineer role focuses on creating and advancing foundation-model and LLM systems, including the software components, evaluation, and production optimization needed to operate at scale.

Location: McLean, VA 22101 (onsite)
Salary: USD 197,300 - 225,100 per year

What you’ll do

• Work with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change 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.
• Apply a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch.
• Introduce state-of-the-art LLM optimization techniques to improve performance and production outcomes, including scalability, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.

Skills and experience we’re looking for

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master’s degree plus at least 2 years of experience developing AI and ML algorithms or technologies.
• At least 4 years of experience programming with Python, Go, Scala, or Java.
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or an equivalent private cloud.
• Experience designing, developing, delivering, and supporting AI services.
• Experience developing AI and ML algorithms or technologies (for example: LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang.
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
• Passion for keeping up with the latest AI research and AI systems, and applying novel techniques judiciously in production.

Technologies you may work with

• AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch
• AWS, Google Cloud, Azure
• Python, Go, Scala, Java, C++, C#, Golang
• Foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, observability, memory

Incentives and benefits

• Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
• A comprehensive, competitive, and inclusive set of health, financial, and other benefits designed to support total well-being.

Additional details

• This role is expected to accept applications for a minimum of 5 business days.
• Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws.
• Capital One promotes a drug-free workplace.
• Candidates hired to work in other locations will be subject to the pay range associated with that location; the annualized salary offered will be reflected in the offer letter.
• For accommodation requests related to applying, contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• For technical support or questions about the recruiting process, email [email protected].
• No agencies please.

Capital One Financial is made up of several different entities. Any position posted in Canada is for Capital One Canada, in the United Kingdom for Capital One Europe, and in the Philippines for Capital One Philippines Service Corp. (COPSSC).