AI Engineer: AI Foundations & LLM Core

Requirements:

• A bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related discipline, plus at least 4 years of experience developing AI and ML algorithms or technologies, or a masters degree in one of those fields plus at least 2 years of relevant experience
• At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java
• Experience leading the development of AI systems, including trade-offs among cost, latency, throughput, and accuracy
• At least 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud environments
• Experience designing, building, delivering, and supporting AI services
• Experience developing AI and ML technologies such as LLM inference, similarity search and vector databases, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang
• Experience applying advanced techniques to optimize training and inference software for better hardware utilization, latency, throughput, and cost
• Experience building agentic AI systems and agentic workflows
• Strong interest in current AI research and the ability to apply novel methods judiciously in production
• Experience designing distributed systems for model training, evaluation, and online inference at petabyte scale
• Experience defining AI model governance processes, including reproducibility, lineage tracking, and automated retraining schedules
• Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms

Responsibilities:

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that improve how our associates work and how our customers interact with Capital One
• Design, build, test, deploy, and support AI software components spanning foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Use open source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, vector databases, PyTorch, and related tools
• Develop and introduce advanced foundation model optimization approaches to improve scalability, cost, latency, and throughput in production AI systems
• Contribute to the technical vision and long-term roadmap for foundational AI systems
• Own the end-to-end architecture for complex AI systems, with emphasis on maintainability, observability, and ethical alignment
• Define and uphold service-level objectives for AI reliability, including latency, uptime, and model performance drift
• Work with infrastructure engineering to improve GPU and TPU utilization and speed up model inference pipelines
• Lead cross-functional technical reviews for new AI system deployments to ensure security, data governance, and compliance standards are met
• Mentor Principal and Senior Associates on scalable design, performance tuning, and translating research into production

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• C#
• Cloud
• CUDA
• Golang
• Hardware
• Support
• Java
• LLM
• Model Training
• PyTorch
• Python
• Scala
• Security
• Machine Learning

More

At Capital One, we are building responsible and reliable AI systems to change banking for good. Our Intelligent Foundations and Experiences team sits at the center of that vision, working closely with partners across the company to advance AI science and engineering and deliver proprietary solutions that create value for millions of customers. We empower teams with AI models and platforms that help them enhance products in scalable and responsible ways. This role includes salary ranges that vary by location, eligibility for performance-based incentives, and comprehensive health, financial, and other benefits designed to support total well-being. We will also consider sponsoring a new qualified applicant for employment authorization for this position.

last updated 43 week of 2026