AI Engineer, MLX & Agentic AI

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 building 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.
• Preferred experience includes leading AI systems where tradeoffs among cost, latency, throughput, and accuracy are considered.
• Preferred experience includes 6 years of deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or similar private cloud environments.
• Preferred experience includes designing, developing, delivering, and supporting AI services.
• Preferred experience includes building AI and ML technologies such as LLM inference, similarity search, vector databases, guardrails, or memory systems using Python, C++, C#, Java, CUDA, or Golang.
• Preferred experience includes applying advanced techniques to optimize training and inference software for better hardware utilization, latency, throughput, and cost.
• Preferred experience includes building agentic AI systems and agentic workflows.
• Preferred experience includes staying current with AI research and applying new techniques thoughtfully in production.
• Preferred experience includes designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• Preferred experience includes defining AI model governance processes, including reproducibility, lineage tracking, and automated retention schedules.
• Preferred experience includes influencing architectural decisions across multiple AI product lines or platforms.

Responsibilities:

• We 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.
• We design, build, test, deploy, and support AI software components such as foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
• We use open source and SaaS AI technologies including AWS Ultraclusters, Hugging Face, VectorDBs, PyTorch, and related tools.
• We create and apply advanced foundation model optimization methods to improve scalability, cost, latency, and throughput in large-scale production AI systems.
• We help shape the technical vision and long-term roadmap for foundational AI systems at Capital One.
• We own end-to-end architecture for complex AI systems, with focus on maintainability, observability, and ethical alignment.
• We define and manage service-level objectives for AI reliability, including latency, uptime, and model performance drift.
• We work with infrastructure engineering to improve GPU/TPU utilization and speed up model inference pipelines.
• We lead cross-functional technical reviews for new AI deployments, 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
• Model Training
• PyTorch
• Python
• Scala
• Security
• Machine Learning

More

We are Capital One, building responsible and reliable AI systems to change banking for good. Our Intelligent Foundations and Experiences (IFX) team sits at the center of our AI vision, partnering across the company to advance science and AI engineering and to build proprietary solutions that serve millions of customers. We offer a comprehensive, competitive, and inclusive benefits package that supports total well-being, along with performance-based incentives. This role includes salary ranges that vary by location, with listed markets including McLean, Cambridge, New York, San Francisco, and San Jose. We may sponsor a new qualified applicant for employment authorization for this position.

last updated 43 week of 2026