Sr. Staff AI Engineer

Capital One; McLean (VA); On-site; USD 180,000 - 240,000; Full time

Job summary

Capital One is seeking a Sr. Staff AI Engineer to help build responsible, scalable AI systems. You will work with the IFX team to design and deploy AI-powered products, optimizing model performance, latency, and cost while ensuring safety and governance across the enterprise.

Lead multi-year platform initiatives, mentor engineering teams, and translate research breakthroughs into production-ready AI infrastructure at Capital One.

Qualifications

• Bachelor's or Master's in CS/AI/EE or related field with extensive AI/ML development experience
• 10+ years of AI/ML development experience (as described)
• Proficiency in Python and at least one of Go/Scala/CUDA/Java

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components including foundation model training and inference
• Leverage Open Source and SaaS AI technologies (AWS Ultraclusters, Huggingface, VectorDBs, PyTorch)
• Invent optimization techniques for foundation models to improve performance and costs
• Contribute to the long-term AI architecture roadmap at Capital One
• Define AI architecture vision and production-ready workflows
• Establish AI performance, safety, and transparency standards
• Drive multi-year platform initiatives unifying data, compute and model lifecycles
• Mentor senior technical leaders across research, data and engineering

Skills

Python

Go

Scala

CUDA

Java

Education

Bachelor's degree in CS/AI/EE or related

Master's degree in CS/AI/EE or related

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

Sr. Staff AI Engineer

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. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy 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 enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

What You'll Do

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
• Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale
• Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide
• Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture
• Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One's AI technical leadership

Basic Qualifications

• Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 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 8 years of experience developing AI and ML algorithms or technologies
• At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java

Preferred Qualifications

• Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy
• 9 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure or equivalent private cloud)
• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems
• Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Experience in building agentic AI systems and agentic workflows
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production
• Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers
• Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership
• Demonstrated experience designing long-term AI infrastructure