Senior Lead AI Engineer (FM Hosting)

Capital One offers a path to build responsible, reliable AI systems that change banking for good. This onsite role in McLean, VA sits on the Intelligent Foundations and Experiences team and offers a competitive compensation package, including a salary range of USD 229,900 to 262,400 per year, comprehensive health and financial benefits, and performance-based incentives. You will work with a cross-functional group of engineers, research scientists, technical program managers, and product managers to deliver AI powered products that impact both colleagues and customers.

Responsibilities

• Collaborate with a cross-functional team to deliver AI enabled products that transform 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.
• Utilize a broad stack of open source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and apply advanced LLM optimization techniques to boost scalability, cost efficiency, latency, and throughput in production AI systems.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.

Requirements

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related field with at least 6 years of experience developing AI and ML algorithms or technologies; or a Master's degree in the same fields with at least 4 years of experience.
• At least 6 years of experience programming with Python, Go, Scala, or Java.

Technologies

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

Benefits

• Health benefits
• Financial benefits
• Other benefits
• Performance-based incentive compensation (cash bonuses and long-term incentives)

Team description

The Intelligent Foundations and Experiences (IFX) team sits at the center of Capital One's AI vision. We collaborate with partners across the company to advance the state of the art in AI engineering and to deploy proprietary solutions that deliver value to millions. Our models and platforms empower teams to enhance products with the power of AI, driving meaningful outcomes across the business.

The ideal candidate

• Enjoys building systems, cares deeply about quality, and is committed to doing the right thing to drive impact in banking.
• Keeps pace with the latest AI research and can translate publications into production-ready techniques when appropriate.
• Adapts quickly, seeks clarity in large, complex problems, asks questions, and communicates findings concisely; comfortable sharing new ideas even when they are unproven.
• Strong technical foundation in engineering and mathematics; able to spot optimization opportunities across hardware, software, and AI to improve performance.
• Resilient trailblazer who can chart new paths to achieve business goals when the route is unclear.

Basic qualifications

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

Preferred qualifications

• 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.
• Demonstrated 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 Go.
• Experience optimizing training and inference software to improve hardware utilization, latency, throughput, and cost.
• Strong interest in AI research and systems, with the ability to judiciously apply novel techniques in production.
• Excellent communication and presentation skills, capable of articulating complex AI concepts to peers.