Gen AI Platform Engineer (LLMs & Orchestration)

Capital One Group; California, Northern (MO, KY); Hybrid; USD 251,000 - 286,000; Full time

Job summary

Capital One in California is seeking an AI Engineer 5 to join the Intelligent Foundations and Experiences (IFX) team, building responsible, scalable AI systems and production-ready AI components.

You will design, develop, test, deploy, and support AI software including foundation model training, LLM inference, agents, vector search, and observability, while optimizing cost, latency, and throughput.

Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI/ML algorithms or technologies, or a Master's degree plus at least 4 years of experience.
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.
• Experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent).

Responsibilities

• 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.
• Invent and introduce state-of-the-art foundation model optimization techniques to improve performance, cost, latency, throughput.
• Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems.

Skills

Python

Go

CUDA

Java

Education

Bachelor's degree in CS/related field

Master's degree in CS/AI

Tools

AWS

HuggingFace

PyTorch

VectorDBs

Job description

Capital One in California is seeking an AI Engineer 5 to join the Intelligent Foundations and Experiences (IFX) team, building responsible, scalable AI systems and production-ready AI components.

You will design, develop, test, deploy, and support AI software including foundation model training, LLM inference, agents, vector search, and observability, while optimizing cost, latency, and throughput.