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# Forward Deployed Engineer

- **Company:** Knak Digital
- **Location:** Washington, DC, United States
- **Contract:** Permanent contract
- **Skills:** Big Data, Python (Programming Language), Large Language Models, Multi-Agent Systems, Build Management, AI Platforms, Machine Learning Operations, Data Pipelines
- **Published:** August 28, 2026
- **Apply:** https://www.wayup.com/i-j-Forward-Deployed-Engineer-Knak-Digital-453610889374018/

## About the Role

1. Able to operate independently in ambiguous, partner-facing settings with technical and operational ownership.
 2. Strong Python engineer with end-to-end ownership experience.
 3. Experience with LLMs and creating agentic systems.
 4. Built or maintained data pipelines and ML infrastructure.
 5. Familiar with RL workflows or simulation environments.
 6. Comfortable in high-security, high-reliability environments.
Preferred Qualifications

 1. Active U.S. security clearance
 2. Experience supporting U.S. Government, defense, intelligence, or national security missions.
 3. Prior experience at a startup, defense organization, Department of War, or government-focused technology company.
 4. Background operating in fast-moving startup environments, mission-critical government settings, or both.

## Description

We're hiring an MTS to work on applied AI systems across research and production. This role spans model experimentation, infrastructure, and deployment in high-assurance, mission-critical environments, including forward-deployed work with strategic partners to ensure mission success.
What You'll Work On

 1. Build and deploy agentic AI systems that support high-impact U.S. Government missions from prototype to production.
 2. Design and integrate LLM applications, including multi-agent systems, tool-using agents, RAG workflows, and human-in-the-loop autonomy.
 3. Work directly with government partners in forward-deployed environments to translate mission needs into technical systems.
 4. Build and maintain large-scale data curation and evaluation pipelines for model training and improvement.
 5. Develop infrastructure for model inference, experimentation, evaluation, and deployment across frontier AI platforms.
 6. Build AI systems that turn mission data, models, and tools into real operational autonomy.
 7. Own systems across the full lifecycle, including discovery, architecture, implementation, deployment, reliability, security, and iteration.


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