AI Infrastructure Engineer | Hybrid

About the role

This is a full-time hybrid position based in Washington, D.C.

Responsibilities

• Build and maintain data pipelines for model training, evaluation, and research workflows.
• Design and run reinforcement learning environments for experimentation and training.
• Develop and scale model inference systems to enhance performance and reliability.
• Implement and maintain software development kits and integrations across frontier AI platforms.
• Construct agentic systems using modern large language model stacks, ensuring security and reliability.
• Collaborate directly with partners in forward-deployed settings on sensitive, high-impact use cases.

Requirements

• Have strong relevant experience as a Python engineer with end-to-end ownership of projects.
• Have experience with large language models or agentic systems, such as LangChain or LangGraph.
• Have built or maintained data pipelines and machine learning infrastructure.
• Be familiar with reinforcement learning workflows or simulation environments.
• Have experience with distributed systems or scaling inference processes.
• Be comfortable operating in high-security and high-reliability environments.

Compensation

$350K - $500K/yr