Triumphant Nerd

Triumphant Nerd is searching for Tactical Edge Software Engineers to develop and deploy advanced AI systems for tactical and operational environments.

This role sits at the intersection of AI, LLMs, autonomy, robotics, and edge computing. You’ll build and deploy specialized models and multi-agent systems that operate on constrained hardware and interface with sensors, effectors, and drone systems. The work supports high-impact defense missions where reliable, untethered AI must function in demanding environments.

What You’ll Do:

• Train and fine-tune LLMs for tactical edge applications
• Optimize AI models and runtimes for GPU, CPU, and specialized accelerator hardware
• Design and implement multi-agent systems for mission scenarios
• Integrate LLM agents with sensors, effectors, and drone systems
• Benchmark and evaluate agent performance, reliability, and capabilities
• Build scalable, reliable, and fail-safe systems for high-stakes environments
• Deploy and maintain production AI systems across constrained edge environments

What We’re Looking For:

• 5+ years of software engineering experience
• 2+ years in system design or architecture
• Strong proficiency in Python, C++, and/or Rust
• Experience building and deploying LLMs and LLM agents
• Hands-on experience with PyTorch, HuggingFace Transformers, LangChain, vLLM, or similar technologies
• Experience optimizing AI models for edge hardware
• Familiarity with Ollama, Mojo, TVM, TensorFlow Lite, and vLLM
• Experience building technically demanding software in defense, aerospace, big tech, drones/robotics, or applied research
• Customer-facing or cross-functional experience
• BS or higher in Computer Science, Physics, Mathematics, or similar
• Eligibility for a U.S. security clearance
• Based in Seattle or willing to relocate (provided)
• Salary up to $275K plus perks!
• Ability to travel up to 25%

Why Join:

• Work on cutting-edge AI and autonomous systems at the tactical edge
• Build technology designed for real-world defense and operational environments
• Collaborate with experts across AI, LLMs, robotics, autonomy, and systems engineering
• Solve challenging problems involving constrained hardware and high-stakes deployments