Lead AI Engineer – AI Foundations

Jobtailor; California (MO); On-site; USD 180,000 - 240,000; Full time

Job summary

Capital One is seeking an experienced AI Software Engineer to partner with engineers, researchers and product managers to deliver AI-powered products. You will design, develop, test, deploy, and support AI components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability.

The role requires staying ahead of AI research, applying novel techniques, and leveraging cloud platforms with open-source

Qualifications

• Bachelor's degree in CS/AI/EE/CE or related fields with 4+ years of AI/ML experience or

Responsibilities

• Partner with engineers, research scientists, tech program managers and product managers to deliver AI-powered products.
• Design, develop, test, deploy and support AI software components including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance and observability.
• Invent and introduce state-of-the-art LLM optimization techniques to improve scalability, cost, latency and throughput of production AI systems.
• Contribute to the technical vision and long-term roadmap of foundational AI systems at Capital One

Skills

Python

Go

Scala

Java

C++

C#

Golang

AI Software Development

LLM Optimization

Cloud Platform Deployment

Education

Bachelor's degree in Computer Science/AI/EE/CE or related field

Master's degree in related fields + 2+ years experience

Tools

AWS Ultraclusters

Hugging Face

VectorDBs

Nemo Guardrails

PyTorch

Job description

• Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability
• Leverage open-source and SaaS AI technologies including AWS Ultraclusters, Hugging Face, VectorDBs, Nemo Guardrails, and PyTorch
• Invent and introduce state-of-the‑art LLM optimization techniques to improve scalability, cost, latency, and throughput of production AI systems
• Contribute to the technical vision and long‑term roadmap of foundational AI systems at Capital One

Requirements

• 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, OR a Master's degree in those fields plus at least 2 years of such experience
• At least 4 years of experience programming with Python, Go, Scala, or Java
• Passion for staying abreast of latest AI research and ability to apply novel techniques in production
• Strong foundation in engineering and mathematics
• Expertise in hardware, software, and AI
• 6 years of experience deploying scalable and responsible AI solutions on cloud platforms is preferred
• Experience designing, developing, delivering, and supporting AI services is preferred
• Experience developing AI and ML algorithms or technologies using Python, C++, C#, Java, or Golang is preferred
• Experience optimizing training and inference software for hardware utilization, latency, throughput, and cost is preferred
• Capital One will consider sponsoring a new qualified applicant for employment authorization

Core Competencies

Demonstrates expertise in developing and deploying AI and ML algorithms, with a strong foundation in engineering and mathematics. Proficient in leveraging cloud platforms and open‑source technologies to optimize AI solutions for scalability, cost, and performance.

Highest-signal resume keywords

• AI Software Development
• Python Programming
• LLM Optimization Techniques
• Cloud Platform Deployment
• AI Algorithm Design

ATS Optimization Keywords

Hard Skills

• AI Algorithms
• Machine Learning
• Python
• Go
• Scala
• Java
• C++
• C#
• Golang
• Mathematics

Soft Skills

• Collaboration
• Passion for AI Research

Industry Keywords

• AI Solutions
• Scalable Systems
• Model Evaluation
• Governance
• Observability

Tools & Technologies

• AWS Ultraclusters
• Hugging Face
• VectorDBs
• Nemo Guardrails
• PyTorch