Role Description
Core team $200K - $300K/yr compensation Required Skills
Agentic AI & LLM Development Python Software Engineering ML Infrastructure & Data Pipelines Forward Deployment & Technical Problem-Solving
About micro1
micro1 is a data lab that helps AI labs & Enterprises train foundational models and agents. We provide frontier evaluations and reinforcement learning environments to improve LLM capabilities, as well as contextual evaluations to monitor and improve AI agents in enterprise settings. Our AI recruiting agent sources and vets domain experts for our data platform that enables rapid production of high-quality training data. Our research spans high-value, specialized domains (legal, medical, finance, coding, etc.), where expert-level data is the hardest to produce and most valuable for advanced model performance. Our pipeline performance system ensures both quality and velocity.
Job Title: Forward Deployed Engineer, U.S. Government
Job Type: Full-time
Location: Greater Washington DC area (onsite requirement 3-4x per week)
The Role
We’re hiring a Forward Deployed Engineer to build and deploy applied AI systems supporting high-impact U.S. Government missions. This role combines software engineering, AI development, and infrastructure deployment in high-assurance, mission-critical environments.
You'll work directly with government partners to translate operational needs into reliable technical solutions, taking ownership from initial prototyping through production deployment and ongoing improvement.
What You'll Work On
- Build and deploy agentic AI systems supporting U.S. Government missions, from prototype to production.
- Develop and integrate LLM applications, including multi-agent systems, tool-using agents, RAG workflows, and human-in-the-loop autonomy.
- Work directly with government partners to understand mission requirements, integrate solutions, and troubleshoot technical challenges.
- Build and maintain Python applications, APIs, data pipelines, and integrations with existing government systems.
- Develop infrastructure for model inference, experimentation, evaluation, and deployment across AI platforms.
- Deploy and maintain AI applications across cloud, on-premises, or restricted environments, ensuring reliability and security.
- Collaborate with engineering and research teams to improve model performance and translate mission feedback into product improvements.
- Own technical solutions throughout their lifecycle, including development, deployment, monitoring, and iteration.
What We're Looking For
- Strong Python engineering skills with hands-on experience building and maintaining production software.
- Experience developing LLM applications, AI agents, or agentic workflows.
- Experience with APIs, data pipelines, system integrations, and backend development.
- Familiarity with cloud infrastructure, containerization, and deployment technologies such as Docker, Kubernetes, or CI/CD pipelines.
- Experience with ML infrastructure, model evaluation, or AI experimentation workflows.
- Ability to independently solve technical problems and deliver solutions in ambiguous, customer-facing environments.
- Strong communication skills and ability to translate operational requirements into working technical systems.
- Comfortable operating in high-security, high-reliability, and mission-critical environments.
Preferred Qualifications
- Active U.S. security clearance or eligibility and willingness to obtain one.
- Experience supporting U.S. Government, defense, intelligence, or national security missions.
- Experience deploying software in restricted, air-gapped, or government cloud environments.
- Familiarity with RL workflows, simulation environments, or advanced AI evaluation techniques.
- Prior experience at a startup, defense organization, Department of War, or government-focused technology company.
- Background operating in fast-moving startup environments, mission-critical government settings, or both.
Compensation & Benefits Notice
The national pay range for this full-time position is base salary of $150,000 –$200,000. All employees are eligible for equity compensation, and employees may also receive performance-based bonuses, dependent on role and subject to company policies. micro1 provides a comprehensive benefits package, including up to 100% reimbursement for health-insurance premiums, paid time off, a 401(K) plan with a company match, and additional benefits designed to support a high-performing, remote-first workforce.
micro1 is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to [email protected].
Our hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
Apply now
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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