Lead AI Engineer: Foundation Models & Responsible AI

Capital One; San Francisco (CA); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking a Lead AI Engineer (AI Foundations) to advance responsible AI systems and scalable ML infrastructure. You will partner with cross-functional teams to deliver AI-powered products and build foundation models, inference, and governance capabilities.

The role emphasizes optimizing training/inference, leveraging open-source and SaaS AI tools, and shaping the long-term AI roadmap at Capital One. Remote/hybrid flexibility may apply in some locations.

Qualifications

• Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies.
• At least 4 years of experience programming with Python, Go, Scala, or Java.
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)
• Experience designing, developing, delivering, and supporting AI services
• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang
• Experience developing and applying state-of-the-<b>???</b> techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost
• Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

Responsibilities

• Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.
• Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.
• Invent and introduce state-of-the-art LLM optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.
• Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

Skills

Python

Go

Scala

Java

AWS

Google Cloud

Azure

LLM Inference

Similarity Search

VectorDBs

Guardrails

Memory

PyTorch

Nemo Guardrails

Education

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Tools

PyTorch

Nemo Guardrails

AWS Ultraclusters

Job description

Capital One is seeking a Lead AI Engineer (AI Foundations) to advance responsible AI systems and scalable ML infrastructure. You will partner with cross-functional teams to deliver AI-powered products and build foundation models, inference, and governance capabilities.

The role emphasizes optimizing training/inference, leveraging open-source and SaaS AI tools, and shaping the long-term AI roadmap at Capital One. Remote/hybrid flexibility may apply in some locations.