Build responsible, scalable AI systems at the center of Capital One’s Intelligent Foundations and Experiences (IFX) organization. This Lead AI Engineer role in McLean, VA (onsite) focuses on foundational AI capabilities, including large language model inference, similarity search, guardrails, evaluation, experimentation, governance, and observability. You will help deliver AI-powered products that improve how associates work and how customers interact with Capital One.
Compensation: USD 197,300 - 225,100 per year (range reflects the location listed above).
What you’ll do
- Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that support business outcomes.
- Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
- Apply a mix of open source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch.
- Develop and introduce state-of-the-art LLM optimization techniques to improve production performance, including scalability, cost, latency, and throughput.
- Help shape the technical vision and long-term roadmap for foundational AI systems at Capital One.
What you bring
- Education and experience: A Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field 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.
- Programming: At least 4 years programming with Python, Go, Scala, or Java.
- Cloud deployment: 6 years deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or an equivalent private cloud.
- Service delivery: Experience designing, developing, delivering, and supporting AI services.
- AI/ML development: Experience developing AI and ML algorithms or technologies (including LLM inference, similarity search and VectorDBs, guardrails, and memory) using Python, C++, C#, Java, or Golang.
- Optimization: Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
- Production mindset: Passion for staying current with AI research and applying novel techniques judiciously in production.
Technologies you’ll work with
- AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch
- AWS, Google Cloud, Azure
- Python, Go, Scala, Java, C++, C#, Golang
- LLM Inference, Similarity Search, Guardrails, Memory
Benefits
- 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 your total well-being.
About the IFX team
The Intelligent Foundations and Experiences (IFX) team brings Capital One’s AI vision to life. The team works closely with partners across the company to advance the state of the art in science and AI engineering, building and deploying proprietary solutions central to the business and delivering value to millions of customers. AI models and platforms from IFX help teams enhance their products with responsible and scalable AI for high-leverage impact.
Additional information: Applications will be accepted for a minimum of 5 business days. No agencies please. Capital One is an Equal Opportunity Employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One may consider qualified applicants with a criminal history consistent with applicable law regarding criminal background inquiries. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. If you need accommodation related to applying, contact Capital One Recruiting at 1-800-304-9102 or RecruitingAccommodation@capitalone.com. For technical support, email Careers@capitalone.com.
Salary ranges vary by location. Candidates hired to work in other locations will receive the pay range associated with that location, and the annualized salary offered at hire will be reflected in the offer letter.
