Lead AI Engineer

Lead AI Engineer to build and deploy responsible, scalable AI systems as part of Capital One’s Intelligent Foundations and Experiences (IFX) team.

Responsibilities

• Collaborate with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associate workflows and customer experiences
• Design, develop, test, deploy, and support AI software components including:
  • Foundation model training
  • Large language model (LLM) inference
  • Similarity search
  • Guardrails
  • Model evaluation
  • Experimentation
  • Governance
  • Observability
• Use a mix of Open Source and SaaS AI tooling such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and related technologies
• Develop and introduce LLM optimization techniques to improve production performance across scalability, cost, latency, and throughput
• Help shape technical vision and the long-term roadmap for foundational AI systems at Capital One

Requirements

• Education plus experience:
  • Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, with at least 4 years of experience developing AI/ML algorithms or technologies, or
  • Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field, with at least 2 years of experience developing AI/ML algorithms or technologies
• At least 4 years of programming experience with Python, Go, Scala, or Java

Technologies

• AWS Ultraclusters
• Huggingface
• VectorDBs
• Nemo Guardrails
• PyTorch
• AWS, Google Cloud, Azure
• Python, Go, Scala, Java
• C++, C#, Golang
• Large language model inference
• Similarity search
• Guardrails
• Model evaluation
• Experimentation
• Governance
• Observability
• Foundation model training
• LLM optimization
• Memory

Team Description

• IFX (Intelligent Foundations and Experiences) is central to bringing Capital One’s AI vision to life
• Partners across the company to advance the state of the art in science and AI engineering
• Builds and deploys proprietary solutions that support the business and deliver value to millions of customers
• Enables teams across Capital One to enhance products with responsible, scalable AI for high-leverage impact

Ideal Candidate

• Enjoys building systems and taking ownership of quality work
• Interested in staying current with the latest research and translating scientific publications into production-ready solutions
• Comfortable with large, undefined problems; asks questions, digs for root causes, and communicates findings clearly
• Willing to propose new ideas even when they are not yet fully proven
• Deeply technical with strong foundations in engineering and mathematics; can identify and pursue optimization opportunities across hardware, software, and AI
• Resilient and able to create new paths to meet business goals when the route is unclear

Preferred Qualifications

• 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/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 to optimize training and inference software for improved hardware utilization, latency, throughput, and cost
• Passion for AI research and AI systems; applies novel techniques judiciously in production

Benefits

• Performance-based incentive compensation, potentially including cash bonus(es) and/or long-term incentives (LTI)
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being

Location: New York, NY (onsite)

Compensation: USD 215,200 - 245,600 per year