Forward Deployed Engineer, U.S. Government
Listing checked October 11, 2026 · pay as published by Micro1
Overview
This full-time role places you at the intersection of applied AI research and real-world deployment for U.S. Government missions. You will build agentic AI systems, LLM applications, and data pipelines that move from prototype to production in high-assurance settings. The position is remote but requires relocating to the DC area for forward-deployed work with strategic partners. Expect to own systems end to end, from discovery and architecture through deployment, reliability, and security.
What You'll Do7
- 1Create and launch agentic AI systems that serve high-impact government missions, guiding them from early prototypes to full production.
- 2Design and connect LLM applications, including multi-agent setups, tool-using agents, RAG workflows, and human-in-the-loop autonomy.
- 3Collaborate directly with government partners in forward-deployed settings to turn mission needs into working technical systems.
- 4Build and maintain large-scale data curation and evaluation pipelines that support model training and ongoing improvement.
- 5Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms.
- 6Construct AI systems that convert mission data, models, and tools into operational autonomy.
- 7Take ownership of systems across the entire lifecycle: discovery, architecture, implementation, deployment, reliability, security, and iteration.
Requirements6
- 1Ability to work independently in ambiguous, partner-facing environments with technical and operational ownership.
- 2Strong Python engineering skills with experience owning projects from start to finish.
- 3Hands-on experience with LLMs and building agentic systems.
- 4Track record of building or maintaining data pipelines or ML infrastructure.
- 5Familiarity with RL workflows or simulation environments.
- 6Comfort operating in high-security or high-reliability environments.
Who Should Apply
The ideal candidate is a Python engineer who has built agentic systems and LLM applications, and who can point to data pipelines or ML infrastructure they have owned end to end. You should be at ease in ambiguous, partner-facing situations and have some exposure to RL workflows or simulation environments. This role suits someone who has worked in high-security or high-reliability settings, or who is ready to do so. It is less suitable for engineers who prefer narrowly defined tasks or who are not willing to relocate to the DC area. Candidates often get rejected when they lack concrete examples of deploying LLM systems to production, or when they cannot show independent ownership of a project from discovery through deployment.
Salary Insight
The pay range for this full-time position is $40 to $60 per hour. The source also mentions a base salary of $150,000 to $250,000, equity compensation, and performance-based bonuses. Benefits include up to 100% health-insurance premium reimbursement, paid time off, and a 401(K) with company match.
Pay and demand for Machine Learning & AI roles
AggregatedTypical pay
$75/hour
This role
$40–$60/hr
Most Machine Learning & AI roles pay $55–$102 per hour. This role's pay sits below that range.
Based on 514 similar roles that publish pay · 96 publish only a top rate; those count at the rate they gave
Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.
- Live similar roles
- 607
- Listed in last 30 days
- 416
- Remote
- 95%
Hiring most right now: micro1 (242) · Mercor (81) · SME Careers (67)
Most requested skills · share of roles
- python20%
- technical writing10%
- llm evaluation7%
- ai evaluation7%
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Compensation
$40–60/hr
Required Skills
Application Tip
In your application, highlight specific projects where you built agentic AI systems or LLM applications, and quantify the impact, such as the number of agents deployed or the scale of data pipelines you managed. Also mention any experience with RL workflows or simulation environments, and state your security clearance status or willingness to obtain one.
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