Hybrid | Forward Deployed Engineer, U.S. Government — $300,000–$500,000/year
About The Position
We are sharing a full-time opportunity for an experienced Forward Deployed Engineer with strong expertise in Python, LLM systems, agentic AI, data pipelines, distributed systems, and production infrastructure to build and deploy mission-critical AI systems supporting U.S. Government environments. The role spans applied AI research, production engineering, infrastructure, and forward-deployed implementation. The successful candidate will work directly with government partners to translate operational requirements into secure, reliable AI systems, taking ownership from discovery and architecture through deployment, reliability, security, and iteration.
Requirements
- Strong Python engineering skills with demonstrated end-to-end ownership
- Experience building production applications using LLMs
- Hands-on experience with agentic or multi-agent AI systems
- Experience building or maintaining data pipelines or ML infrastructure
- Strong understanding of distributed systems
- Familiarity with reinforcement-learning workflows or simulation environments
- Comfortable operating in high-security, high-reliability, or mission-critical environments
- Strong ability to work independently in ambiguous, partner-facing situations
- Active U.S. security clearance is highly advantageous
- Candidates eligible and willing to obtain a U.S. security clearance may also be considered
Nice To Haves
- Experience supporting U.S. Government, defence, intelligence, or national-security missions is preferred
- Experience in startups, defence organisations, government-focused technology companies, or comparable fast-moving environments is beneficial
Responsibilities
- Build and deploy advanced AI systems supporting high-impact U.S. Government missions
- Work directly with government partners in forward-deployed environments
- Translate mission requirements into practical technical systems
- Take projects from prototype and experimentation through production deployment
- Maintain strong technical and operational ownership in ambiguous partner-facing environments
- Design and integrate production-grade LLM applications
- Build multi-agent and tool-using AI systems
- Develop retrieval-augmented generation workflows
- Implement human-in-the-loop autonomy where appropriate
- Convert mission data, models, and tools into operational AI capabilities
- Build and maintain large-scale data-curation pipelines
- Develop evaluation infrastructure for model training and improvement
- Create systems supporting inference, experimentation, evaluation, and deployment
- Maintain scalable ML and data workflows across advanced AI platforms
- Support reliable operation as mission and model requirements evolve
- Design and operate distributed systems in high-reliability environments
- Own architecture, implementation, deployment, and production iteration
- Build systems with security, resilience, and operational continuity in mind
- Diagnose system failures and improve reliability and performance
- Apply sound engineering judgement to infrastructure and deployment trade-offs
- Operate independently in high-security and high-assurance environments
- Collaborate with technical, operational, and government stakeholders
- Maintain ownership throughout the full system lifecycle
- Adapt rapidly as mission requirements and partner needs evolve
- Balance development speed with security, reliability, and operational effectiveness
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
