Senior Lead AI Engineer

Capital One seeks a Senior Lead AI Engineer to guide GenAI Platform Services, overseeing the design, development, and optimization of AI software components and foundational AI systems. The role collaborates with cross functional teams to deliver AI powered products and scalable, responsible AI solutions. Location: McLean, VA onsite. Compensation: USD 229,900 - 262,400 annually. Education and experience requirements include a Master’s degree with at least 4 years of AI/ML experience (or a Bachelor’s with at least 6 years) and a minimum of 6 years of programming experience in Python, Go, Scala, or Java.

Overview

Capital One is focused on building responsible and reliable AI systems that drive innovations in banking for good. The company has a history of using machine learning to deliver real-time, personalized experiences while leveraging strong technology infrastructure and top talent. This foundation positions Capital One at the forefront of enterprises adopting AI at scale, enabling capabilities that support customers and colleagues alike.

Responsibilities

• Collaborate with a cross functional team of engineers, research scientists, technical program managers, and product managers to deliver AI powered products that transform 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.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and apply state of the art LLM optimization techniques to improve performance metrics such as scalability, cost, latency, and throughput in large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Technologies

• AWS Ultraclusters
• Huggingface
• VectorDBs
• Nemo Guardrails
• PyTorch

Benefits

• Health benefits
• Financial benefits
• Performance based incentive compensation

Team Description

The Intelligent Foundations and Experiences (IFX) team centers Capital One's AI initiatives, partnering across the company to advance AI science and engineering. The team builds and deploys proprietary solutions central to the business, delivering value to millions of customers. AI models and platforms empower Capital One teams to enhance products with AI capabilities across the organization.

The Ideal Candidate

• Enjoys building robust systems and takes pride in high quality work while upholding ethical and responsible AI practices.
• Keeps abreast of the latest AI research and can translate scientific publications into production ready approaches.
• Adapts quickly, brings clarity to complex problems, asks insightful questions, and communicates findings concisely; willing to share new ideas even when unproven.
• Is deeply technical with a strong foundation in engineering and mathematics, capable of spotting optimization opportunities across hardware, software, and AI domains.
• Acts as a resilient pioneer who can forge new paths to achieve business goals in uncertain environments.

Basic Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field with at least 6 years of AI/ML development experience, or Master’s degree in the same fields with at least 4 years of AI/ML development experience
• At least 6 years of programming experience in Python, Go, Scala, or Java

Preferred Qualifications

• 7 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, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholders
• Experience developing AI and ML algorithms or technologies (eg LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Strong interest in AI research and practical application of novel techniques in production
• Excellent communication and presentation skills, with ability to articulate complex AI concepts to peers