Senior Lead AI Engineer (Gen AI Platform Services)

The Senior Lead AI Engineer will design, build, and deploy AI software components while shaping the long term roadmap for foundational AI systems, guiding cross functional teams to deliver AI powered products at Capital One.

Overview

Capital One is advancing responsible and reliable AI systems to transform banking for the better. The company has established itself as a leader in applying machine learning to deliver real time, personalized experiences, supported by strong technology infrastructure and top talent. This role contributes to those efforts by building scalable AI platforms and driving impactful AI initiatives across the business.

Team Description

The Intelligent Foundations and Experiences (IFX) team sits at the core of Capital One's AI strategy. The team collaborates with partners across the organization to push the boundaries of AI engineering, deploying proprietary solutions that power products used by millions of customers. AI models and platforms created by the team enable other teams to enhance offerings through AI capabilities.

The Ideal Candidate

• Enjoys building robust systems and takes pride in delivering high quality work, while pursuing responsible and ethical AI outcomes.
• Keeps up with the latest research and can translate academic ideas into production ready solutions.
• Adapts quickly, brings clarity to complex problems, asks insightful questions, and communicates findings concisely. Willing to propose new ideas, even if unproven.
• Strong technical foundation in engineering and mathematics; capable of recognizing optimization opportunities across hardware, software, and AI components.
• Resilient and able to chart new paths to meet business objectives when routes are unclear.

Responsibilities

• Collaborate with engineers, research scientists, 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 mix of Open Source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, Nemo Guardrails, PyTorch, and related tools.
• Develop and apply state of the art LLM optimization techniques to improve scalability, cost efficiency, latency, and throughput in production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Technologies

• AWS Ultraclusters
• Hugging Face
• Vector databases
• Nemo Guardrails
• PyTorch

Location

McLean, VA on site

Salary

Annual salary range: USD 229,900 to 262,400

Basic Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies
• 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 (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 (e.g., 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 staying current with AI research and applying novel techniques in production
• Excellent communication and presentation skills, with the ability to explain complex AI concepts to peers

Benefits

• Health, financial and other benefits supporting overall well being
• Performance-based incentive compensation eligibility (cash bonuses and or long term incentives)