Senior Lead AI Engineer (FM Hosting)

Capital One offers an onsite Senior Lead AI Engineer (FM Hosting) role in New York, NY within the Intelligent Foundations and Experiences (IFX) team. You will design, build, deploy, and optimize AI software components and foundational AI systems to power scalable, real-time customer experiences. The position emphasizes responsible AI, strong engineering fundamentals, and collaborative cross-functional work. Compensation ranges from USD 250,800 to 286,200 per year, plus performance-based incentives and a comprehensive benefits package that supports health, financial security, and total well-being.

Benefits

• Health benefits
• Financial benefits
• Other benefits that support your total well-being
• Performance-based incentive compensation (cash bonuses and/or long term incentives)

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 scalability, cost, latency, and throughput of large-scale production AI systems.
• Contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.

Requirements

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

Technologies

• AWS Ultraclusters
• Huggingface
• VectorDBs
• Nemo Guardrails
• PyTorch
• Python
• C++,
• C#,
• Java,
• Go

Overview

Capital One is committed to building responsible and reliable AI systems that advance banking for good. The company has a long-standing leadership role in applying machine learning to real-time, personalized customer experiences and continues to invest in technology infrastructure and top engineering talent. This role sits at the intersection of AI research and production, helping to scale innovative solutions that impact millions of customers.

Team Description

The Intelligent Foundations and Experiences team is central to Capital One's AI strategy. We partner across the organization to push the boundaries of AI science and engineering, deploying proprietary solutions that drive business value and deliver meaningful experiences to customers. Our models and platforms empower teams across Capital One to leverage AI at scale.

The Ideal Candidate

• You enjoy building systems, take pride in quality, and share a commitment to doing the right thing. You want to tackle problems that can change banking for good.
• You stay current with the latest research and can translate publications into practical production techniques.
• You adapt quickly, bring clarity to big unknowns, ask insightful questions, and articulate findings concisely. You contribute new ideas, even when unproven.
• You are deeply technical with a solid foundation in engineering and mathematics, and you see optimization opportunities across hardware, software, and AI.
• You are a resilient trailblazer who forges new paths to achieve business goals when the route is unclear.

Preferred Qualifications

• 7 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, integrating, delivering, and supporting complex AI systems
• Proven ability to lead and mentor an engineering team and influence cross-functional stakeholders
• Experience developing AI and ML algorithms or technologies (e.g., LLM inference, similarity search and vector databases, guardrails, memory) using Python, C++, C#, Java, or Go
• Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Strong interest in AI research and the practical application of novel techniques in production
• Excellent communication and presentation skills, with the ability to explain complex AI concepts to peers