Capital One seeks a Lead AI Engineer focused on AI Foundations to design, build, deploy, and sustain AI software components, including foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability. The role collaborates with cross-functional teams to shape the technical vision for foundational AI systems, leveraging Open Source and SaaS AI technologies. This onsite position is based in McLean, Virginia, with a salary range of USD 197,300 to 225,100 per year.
Summary
In this senior engineering role, you will lead efforts to design, develop, and support AI software components spanning foundation model training, large language model inference, similarity search, governance, evaluation, experimentation, and observability. You will contribute to Capital One's technical direction for foundational AI systems and work closely with engineers, researchers, program managers, and product managers to deliver AI powered products that impact both associates and customers.
Responsibilities
- Collaborate with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI driven products that transform how associates work and how customers interact with Capital One.
- Design, develop, test, deploy, and maintain AI software components including foundation model training, LLM inference, similarity search, guardrails, evaluation, experimentation, governance, and observability.
- Utilize a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, Nemo Guardrails, PyTorch, and others.
- Create and apply advanced LLM optimization techniques to enhance production AI systems in terms of scalability, cost, latency, and throughput.
- Contribute to the technical vision and the long term roadmap for foundational AI systems at Capital One.
Requirements
- A master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields with at least 2 years of relevant AI/ML development experience, or a bachelor's degree in the same fields with at least 4 years of related experience.
- At least four years of programming experience in Python, Go, Scala, or Java.
Technologies
- AWS Ultraclusters
- Hugging Face
- VectorDBs
- Nemo Guardrails
- PyTorch
Benefits
- Health, financial, and other benefits that support total well-being.
- Performance-based incentive compensation, including cash bonuses and long-term incentives.
Overview
Capital One is dedicated to building responsible and reliable AI systems that advance banking for good. The company has long led in applying machine learning to deliver real-time, personalized customer experiences and continues to invest in technology infrastructure and top talent. This focus positions Capital One at the forefront of enterprise AI, enabling capabilities that range from explaining charges to answering customer questions in real time.
Team Description
The Intelligent Foundations and Experiences (IFX) team sits at the core of bringing Capital One's AI vision to life. We partner across the organization to push the boundaries of AI research and engineering, building and deploying proprietary solutions that drive value for millions of customers. Our AI models and platforms empower teams to enhance products with AI, delivering measurable impact across the business.
The Ideal Candidate
- Enjoys building scalable systems and takes pride in delivering high-quality work that advances banking outcomes.
- Maintains a strong interest in the latest AI research and can translate publications into production-ready approaches.
- Adapts quickly to ill-defined problems, asks the right questions, and communicates findings clearly while proposing new ideas when appropriate.
- Is deeply technical with a solid foundation in engineering and mathematics, leveraging hardware, software, and AI to uncover optimization opportunities.
- Actively pursues a trailblazing path to achieve business goals when the route is uncertain.
Preferred Qualifications
- Six or more years deploying scalable and responsible AI solutions on cloud platforms (AWS, Google Cloud, Azure, or equivalent private cloud).
- Experience designing, developing, delivering, and supporting AI services.
- Proven work on AI and ML algorithms or technologies (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 staying current with AI research and systems and applying novel techniques in production.
