Tactical Edge Software Engineer

Triumphant Nerd; Seattle (WA); On-site; USD 165,000 - 275,000; Full time

Job summary

Triumphant Nerd seeks Tactical Edge Software Engineers to develop and deploy advanced AI systems for tactical environments. The role merges AI, LLMs, autonomy, robotics, and edge computing, building models and multi-agent systems on constrained hardware and with sensor interfaces.

Requirements include 5+ years in software engineering, 2+ years in system design, and proficiency in Python/C++/Rust. Candidates should have experience with PyTorch, HuggingFace Transformers, LangChain, vLLM, and edge

Qualifications

• 5+ years of software engineering experience.
• 2+ years in system design or architecture.
• 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 in defense, aerospace, drones/robotics, or applied research.

Responsibilities

• Train and fine-tune LLMs for tactical edge applications.
• Optimize AI models and runtimes for GPU, CPU, and specialized accelerators.
• 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.

Skills

Software engineering

System design

Cross-functional collaboration

Security clearance eligibility

Education

BS or higher in CS/Physics/Math

Tools

Python

C++

Rust

PyTorch

HuggingFace Transformers

LangChain

vLLM

Ollama

Mojo

TVM

Job description

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