Remote Forward-Deployed AI Engineer | RL & LLM Systems

Crossing Hurdles; United States; Remote; USD 350,000 - 500,000; Full time

Job summary

Crossing Hurdles is seeking a Member of Technical Staff, Forward Deployed (US Gov) to own and advance data-driven AI systems remotely. You will build data pipelines for model training, evaluation, and research, and design reinforcement learning environments for experimentation and deployment.

Refine and scale model inference, implement SDKs across frontier AI platforms, and construct agentic systems using LangChain/LangGraph while maintaining strong security and reliability in high-assurance

Qualifications

• Proficient Python engineer with end-to-end project ownership.
• Experience with large language models and agentic systems (LangChain/LangGraph).
• Built or maintained data pipelines and ML infrastructure.
• Familiar with reinforcement learning workflows or simulation environments.
• Experience with distributed systems or scaling inference.
• Comfortable operating in high-security and high-reliability environments.

Responsibilities

• Build and maintain data pipelines for model training, evaluation, and research.
• 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.
• Transition systems from prototype to production while maintaining high standards of reliability and security.

Skills

Python

End-to-end ownership

Reinforcement learning

Tools

LangChain

LangGraph

Job description

Crossing Hurdles is seeking a Member of Technical Staff, Forward Deployed (US Gov) to own and advance data-driven AI systems remotely. You will build data pipelines for model training, evaluation, and research, and design reinforcement learning environments for experimentation and deployment.

Refine and scale model inference, implement SDKs across frontier AI platforms, and construct agentic systems using LangChain/LangGraph while maintaining strong security and reliability in high-assurance