Lead AI Engineer

As a Lead AI Engineer on Capital One’s Intelligent Foundations and Experiences (IFX) team, you will help build and deploy responsible, scalable AI systems and foundational AI capabilities. The role emphasizes AI software components and production LLM optimization to improve performance across key operating metrics.

Role Overview

The IFX team brings the company’s AI vision to life by advancing state-of-the-art science and AI engineering. In this role, you will contribute to technical foundations that enable teams across Capital One to enhance products using AI in responsible and scalable ways, delivering high-leverage impact to millions of customers.

Key Responsibilities

• Collaborate with cross-functional partners including engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how associates work and how customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components such as 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, including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, and PyTorch, along with cloud platforms such as AWS, Google Cloud, and Azure.
• Develop and introduce state-of-the-art 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 for foundational AI systems at Capital One.

Required Qualifications

• 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 in a related field 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.

Preferred Qualifications

• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• Experience designing, developing, delivering, and supporting AI services.
• Experience developing AI and ML algorithms or technologies such as LLM inference, similarity search and VectorDBs, guardrails, and 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 staying current with AI research and AI systems, and applying novel techniques judiciously in production.

Technology Stack

• AWS Ultraclusters
• Huggingface
• VectorDBs
• Nemo Guardrails
• PyTorch
• AWS, Google Cloud, Azure
• Programming: Python, Go, Scala, Java, C++, C#, Golang
• LLM and AI capabilities: Large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, observability, foundation model training, LLM optimization, memory

Compensation and Benefits

• Salary range: USD 215,200 to 245,600 per year.
• Incentive compensation: Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI).
• Benefits: A comprehensive, competitive, and inclusive set of health, financial, and other benefits to support overall well-being.

Team and Work Style

• Work hand-in-hand with internal partners to advance AI engineering and science.
• Build and deploy proprietary solutions central to the business, with value for millions of customers.
• Focus on responsible and scalable deployment of AI models and platforms across Capital One.