AI Foundations Engineer – Scalable LLM & Systems

Capital One; Cambridge (MA); On-site; USD 269,000 - 307,000; Full time

Benefits offered by this job

Health benefits

Comprehensive benefits package

Job summary

Capital One is seeking an experienced AI Engineer to help build responsible and reliable AI systems that transform banking. You will lead AI software development, optimize large-scale models, and work across teams to deploy cutting-edge AI capabilities in production.

The role emphasizes collaboration with engineers, researchers, and product teams, and demands deep technical expertise in AI, systems, and cloud platforms.

Qualifications

• 8+ years of AI/ML algorithm development or related experience, with a relevant degree.
• 8+ years programming in Python, Go, Scala, or Java.
• Experience deploying scalable AI solutions on cloud platforms (AWS, GCP, Azure).
• Strong communication and leadership skills.

Responsibilities

• Partner with cross-functional engineers, researchers, PMs, and product managers to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including LLMs, retrieval, guardrails, and observability.
• Leverage a broad stack of Open Source and SaaS AI technologies (e.g., HuggingFace, PyTorch, VectorDBs).
• Invent and apply state-of-the-art LLM optimization techniques to improve performance, latency, and cost.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One.

Skills

Python

Go

Scala

Java

Machine Learning

Engineering leadership

Mathematics

Education

Bachelor's degree in CS/AI/EE/CE

Master's degree in CS/AI/EE/CE

Tools

AWS

Google Cloud

Azure

VectorDBs

Nemo Guardrails

HuggingFace

PyTorch

Job description

Capital One is seeking an experienced AI Engineer to help build responsible and reliable AI systems that transform banking. You will lead AI software development, optimize large-scale models, and work across teams to deploy cutting-edge AI capabilities in production.

The role emphasizes collaboration with engineers, researchers, and product teams, and demands deep technical expertise in AI, systems, and cloud platforms.