Lead AI Engineer (AI Foundations)

Lead AI Engineer (AI Foundations) builds responsible, reliable AI systems and advances foundation-model and LLM capabilities to improve customer and associate experiences.

Responsibilities

• Collaborate with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products.
• 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
• Use a stack of open source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch.
• Develop state-of-the-art LLM optimization techniques to improve production performance, including scalability, cost, latency, and throughput.
• Help define the technical vision and contribute to the long-term roadmap for foundational AI systems at Capital One.

Requirements

• 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 (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
• Experience designing, developing, delivering, and supporting AI services.
• Experience developing AI and ML algorithms or technologies (e.g., 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.
• Interest in staying current with AI research and AI systems, and applying novel techniques judiciously in production.

Technologies

• 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).
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being.

Salary and Location

• McLean, VA 22101 (onsite): USD 197,300 - 225,100 per year
• Cambridge, MA: $197,300 - $225,100 per year
• New York, NY: $215,200 - $245,600 per year
• San Jose, CA: $215,200 - $245,600 per year
• Candidates hired to work in other locations will be subject to the pay range associated with that location; the annualized salary offered is reflected in the offer letter.
• This role may be eligible for performance-based incentive compensation, including cash bonus(es) and/or LTI; incentives could be discretionary or non-discretionary depending on the plan.

Additional Information

• Expected to accept applications 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 will consider qualified applicants with a criminal history in a manner consistent with applicable laws.
• Accommodation requests: contact Capital One Recruiting at 1-800-304-9102 or [email protected].
• Technical support or questions about recruiting process: [email protected].
• Capital One does not provide, endorse, or guarantee and is not liable for third-party products, services, educational tools, or other information available through the site.
• Entity note: positions posted in Canada, the United Kingdom, and the Philippines are for their respective Capital One entities.