Join Applied Intuition as a Software Engineer to tackle autonomy challenges in physical AI and contribute to defense operations.
Posted by employer 1 week ago
First seen on Joblaze 6 days ago
Last verified on the company career page 22 hours ago
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Not disclosed in this posting: compensation.
Benefits
Joblaze summary
In this role, the software engineer focuses on developing and enhancing simulation products that support multi-domain autonomous defense operations. Key skills include proficiency in C++ and Python, along with a solid foundation in systems programming and real-time simulation. This position is suitable for engineers with at least three years of experience who have a strong interest in autonomy and robotics, and who thrive in fast-paced, high-stakes environments. The Ann Arbor team operates at the intersection of commercial technology and defense requirements, offering a unique opportunity to impact national security.
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From the original posting
Applied Intuition is rapidly scaling its defense product ecosystem in Ann Arbor! We're looking for talented backend engineers at all levels, who are ready to work on some of the hardest autonomy challenges in physical AI today.
You'll be a core contributor to our flagship simulation products, building the foundational systems that power the development of multi-domain autonomous defense operations . This is not a maintenance role. You'll architect, implement, and own backend infrastructure that runs at the edge of what's technically possible, in environments where the stakes are real.
The Ann Arbor team sits at the intersection of Applied's commercial technology velocity and defense-grade requirements, giving you access to a rapidly evolving product suite and real world impact. You'll work in small, high-ownership teams where your code ships, your decisions matter, and your impact on national security is direct.
Design and implement high-performance software for Axion, Applied Intuition's defense tooling and data platform
Build and extend simulation environments and virtual worlds that enable autonomous systems to be tested and validated before real-world deployment
Develop scalable infrastructure that supports multi-domain autonomous operations — from unmanned ground and aerial platforms to broader joint-force integration scenarios
Partner with autonomy researchers, product teams, and defense customers to translate mission requirements into robust, mission-ready software solutions
Own end-to-end execution of engineering workstreams; from architecture through deployment
Interface with DoD programs and defense customers to ensure solutions meet real-world operational demands
3 + years Professional engineering experience , ideally with C++
Solid software engineering fundamentals: systems programming, concurrency, performance optimization, and real-time rendering or simulation pipelines
Genuine interest in simulation, autonomy, robotics, or physical AI — you want to understand how your software connects to machines operating in the real world
Exposure to or curiosity about multi-domain defense systems — you don't need a defense pedigree, but you're excited to develop one
Strong CS/CE/EE (or similar) foundation; you think rigorously about correctness and performance
Python proficiency for tooling, scripting, and integration work
Comfort with ambiguity; you drive clarity and progress in fast-moving, high-stakes environments
Excellent communication skills; you can explain hard technical tradeoffs to both engineers and non-technical stakeholders
Experience with Unreal Engine or other real-time simulation/game engine environments (e.g., Unity, Gazebo, or custom simulation stacks)
Prior work in simulation for autonomy, robotics, gaming, or defense applications
Familiarity with sensor simulation, synthetic data generation, or physics-based environments
Experience with distributed systems or real-time data pipelines in constrained environments
Must be a U.S. Citizen
Must hold or be eligible for a U.S. Secret security clearance
For more information about U.S. security clearances: click here.
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