[Hiring] Staff AI Engineer @Capital One

Role Description

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. Our investments in technology infrastructure and world-class talent position us to be at the forefront of enterprises leveraging AI.

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.

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.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents, and multi-agent workflows.
• 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 performance of large scale production AI systems.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.
• Set the technical direction for enterprise-wide AI architecture.
• Own the design and integration of model routing, caching, and orchestration systems.
• Champion responsible AI principles across all system design.
• Drive internal education, mentorship, and dissemination of best practices.

Qualifications

• Bachelor'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, or a Master's degree in the same fields plus at least 6 years of experience.
• At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java.

Requirements

• Experience designing AI systems with tradeoff decisions around cost, latency, throughput, and accuracy.
• 8 years of experience deploying scalable and responsible AI solutions on cloud platforms.
• Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems.
• Demonstrated ability to lead and mentor multiple engineering teams.
• Experience developing AI and ML algorithms or technologies using various programming languages.
• Experience developing and applying state-of-the-art techniques for optimizing training and inference software.
• Experience in building agentic AI systems and workflows.
• Excellent communication and presentation skills.
• Proven track record of defining and operationalizing enterprise AI architecture standards.
• Experience leading federated or multi-cloud AI strategies.
• Demonstrated success influencing research-to-production promotion processes.
• Experience defining north-star metrics for AI systems.
• Experience right-sizing models, instance counts, and hardware types given requirements.

Benefits

• Comprehensive, competitive, and inclusive set of health, financial, and other benefits.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.