Forward-Deployed AI Engineer for Mission-Critical Government

micro1; Washington; On-site; USD 120,000 - 190,000; Full time

Job summary

micro1 is seeking a Forward Deployed Engineer to work on applied AI systems for U.S. Government missions. The role spans model experimentation, infrastructure, and deployment in high-assurance environments, including forward-deployed work with strategic partners.

You will design and deploy agentic AI systems, integrate multi-agent and tool-using architectures, and manage data pipelines and ML infrastructure for production-grade reliability and security.

Qualifications

• Strong Python engineer with end-to-end ownership experience.
• Experience with LLMs and creating agentic systems.
• Built or maintained data pipelines / ML infrastructure.
• Familiar with RL workflows or simulation environments.
• Comfortable in high-security / high-reliability environments.

Responsibilities

• Build and deploy agentic AI systems from prototype to production for high-impact missions.
• Design and integrate LLM applications, including multi-agent systems and RAG workflows.
• Collaborate with government partners in forward-deployed environments to translate mission needs into technical systems.
• Develop data curation and evaluation pipelines for model training and improvement.
• Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms.
• Own systems across the full lifecycle, including discovery, architecture, implementation, deployment, reliability, security, and iteration.

Skills

Python programming

LLMs

Agentic systems

Data pipelines

RL workflows

Security/compliance

Tools

ML infrastructure

Inference servers

Job description

micro1 is seeking a Forward Deployed Engineer to work on applied AI systems for U.S. Government missions. The role spans model experimentation, infrastructure, and deployment in high-assurance environments, including forward-deployed work with strategic partners.

You will design and deploy agentic AI systems, integrate multi-agent and tool-using architectures, and manage data pipelines and ML infrastructure for production-grade reliability and security.