AI Engineer - Mc Lean

Requirements:

• We require a bachelors degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field 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 experience developing AI and ML algorithms or technologies.
• We require at least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.
• We value experience leading AI system development with trade-off decisions around cost, latency, throughput, and accuracy.
• We prefer 6 years of experience deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
• We look for experience designing, building, delivering, and supporting AI services.
• We value 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.
• We prefer experience applying state-of-the-art techniques to optimize training and inference software for better hardware utilization, latency, throughput, and cost.
• We value experience building agentic AI systems and agentic workflows.
• We prefer proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale.
• We value experience defining AI model governance processes, including reproducibility, lineage tracking, and automated retraining schedules.
• We look for a demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.
• We value a strong foundation in engineering and mathematics, along with the ability to understand scientific publications and apply new techniques thoughtfully in production.

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, 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.
• We leverage open-source and SaaS AI technologies such as AWS Ultraclusters, Hugging Face, vector databases, PyTorch, and related tools.
• We invent and introduce advanced foundation model optimization techniques to improve performance, scalability, cost, latency, and throughput in large-scale production AI systems.
• We contribute to the technical vision and long-term roadmap for foundational AI systems at Capital One.
• We own the end-to-end architecture for complex AI systems, with a focus on 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 deployments, ensuring security, data governance, and compliance standards 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

We are Capital One, creating responsible and reliable AI systems to change banking for good. Our Intelligent Foundations and Experiences team sits at the center of our AI vision, working closely with partners across the company to advance science and AI engineering and to build proprietary solutions that serve millions of customers. We invest heavily in technology infrastructure, world-class talent, and machine learning expertise to deliver scalable, high-performance AI experiences. This role includes location-based salary ranges for Cambridge, McLean, New York, and San Jose, and is eligible for performance-based incentive compensation and a comprehensive benefits package. We also provide equal opportunity employment, consider sponsorship for qualified applicants, and support reasonable accommodations where needed.

last updated 43 week of 2026