AI Engineer Foundations

Requirements:

• We require 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.
• We require at least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
• We prefer candidates with experience leading AI system development where tradeoffs among cost, latency, throughput, and accuracy are considered.
• We prefer 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or comparable private cloud environments.
• We prefer experience designing, developing, delivering, and supporting AI services.
• We prefer experience developing AI and ML technologies such as LLM inference, similarity search and VectorDBs, guardrails, and memory using Python, C++, C#, Java, CUDA, or Golang.
• We prefer experience applying modern techniques to optimize training and inference software for better hardware utilization, latency, throughput, and cost.
• We prefer experience building agentic AI systems and agentic workflows.
• We prefer strong familiarity with current AI research and the ability to apply new techniques thoughtfully in production.
• We prefer experience designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• We prefer experience defining AI governance processes, including reproducibility, lineage tracking, and automated retention schedules.
• We prefer demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

Responsibilities:

• We partner with cross-functional teams of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for our associates and customers.
• We design, build, test, deploy, and support AI software components, including foundation model training, large language model inference, agents, multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• We work with open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, VectorDBs, and PyTorch.
• We create and apply advanced foundation model optimization methods to improve scalability, cost, latency, and throughput for large-scale production AI systems.
• We contribute to the technical direction and long-term roadmap for foundational AI systems.
• We own end-to-end architecture for complex AI systems, with attention to maintainability, observability, and ethical alignment.
• We define and maintain service-level objectives for AI reliability, including latency, uptime, and model performance drift.
• We collaborate with infrastructure engineering to improve GPU and TPU utilization and speed up model inference pipelines.
• We lead cross-functional technical reviews for new AI system releases, ensuring security, data governance, and compliance expectations are met.
• We 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
• Machine Learning
• Model Training
• PyTorch
• Python
• Scala
• Security

More

At Capital One, we are building responsible and reliable AI systems to help change banking for good. Our Intelligent Foundations and Experiences (IFX) team sits at the center of our AI vision, working closely with partners across the company to advance science and AI engineering and to deliver proprietary solutions that create value for millions of customers. We invest in technology infrastructure, world-class talent, and machine learning expertise to deliver scalable, high-performance AI capabilities with meaningful product experiences. This role is based in Cambridge, MA, New York, NY, or San Jose, CA, and the position may be eligible for performance-based incentive compensation and a comprehensive benefits package that supports total well-being. We also note that we may consider sponsoring a new qualified applicant for employment authorization for this position.

last updated 43 week of 2026