Senior Lead AI Engineer (LLM Gateway, FM Hosting)

Capital One offers a role focused on responsible, scalable AI systems within the Intelligent Foundations and Experiences (IFX) team. This onsite position in McLean, VA combines hands on AI engineering with cross functional collaboration, mentorship opportunities, and a path to influence how associates work and how customers interact with Capital One. Compensation ranges from USD 229,900 to 262,400 per year. A Master’s degree is required, along with meaningful experience in AI and ML development.

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real time, personalized customer experiences. Our investments in technology infrastructure and world class talent, along with our deep experience in machine learning, position us to be at the forefront of enterprises leveraging AI.

Team

The Intelligent Foundations and Experiences (IFX) team sits at the center of bringing our AI vision to life. We partner across the company to advance the state of the art in AI science and engineering, building and deploying proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enrich their products with the transformative power of AI.

Responsibilities

• Collaborate with a cross functional group 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.
• Utilize 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 for production AI systems.
• Contribute to the technical vision and the long term roadmap of Capital One's foundational AI systems.

Requirements

• You love building systems, take pride in code quality, and want to work on problems that can transform banking for good.
• Strong enthusiasm for keeping up with AI research and the ability to translate findings into production solutions.
• Adaptable and capable of clarifying large, undefined problems; you ask questions, dig deep, and communicate findings clearly; you are willing to propose new ideas, even if unproven.
• Deep technical foundation in engineering and mathematics; expertise across hardware, software, and AI to spot optimization opportunities others may miss.
• Resilient and proactive in forging new paths to meet business goals when the path is unclear.
• Education and experience: a Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 6 years of AI/ML development experience, or a Master’s degree with at least 4 years of AI/ML development experience.
• At least 6 years of experience programming with Python, Go, Scala, or Java.
• 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (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 (LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang.
• Experience advancing 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 in production.
• Excellent communication and presentation skills to explain complex AI concepts to peers.

Technologies

• Python
• Go
• Scala
• Java
• PyTorch
• Huggingface
• AWS Ultraclusters
• VectorDBs
• Nemo Guardrails

Benefits

• Performance based incentive compensation (cash bonuses and or long term incentives)
• Health, financial and other benefits that support total well being