Comand AI's mission is to build next-generation C2 software with real users in real deployments in the field. We are fully indexed on the success of every single user, which means the software you ship runs inside live defense operations, not a benchmark.
You'd be joining the engineering team working directly with the leadership. You take a problem, explore it, come back with proposals, and iterate; nobody hands you a fully specified ticket. Most of the team genuinely values that exposure. It isn't a dealbreaker if you're very strong but less drawn to it, but expect real user contact to be part of the job.
What this looks like in practice:
Own end-to-end features on Prevail, our operational planning platform, from scoping through shipping
Work on real geospatial problems: everything in the product lives on a map, so you'll move data between backend and frontend through tile servers and lean on PostGIS for geo queries that need to be genuinely smart
Build and harden ML/LLM workflow orchestration: most product workflows carry an LLM or ML step, so you'll design for retries, queueing, and long-running jobs with LangGraph and LangChain
Design for on-prem and appliance deployment: our default target isn't cloud-native, it's hardware plus software shipped as an appliance, so you're thinking about resource constraints instead of adding another Lambda
Spend time with users in the field when a deployment calls for it
We filter hardest on mission drive, low ego, and resilience under pressure. We want people who reason from first principles rather than lean on memorized patterns, and who ship rather than over-plan.
Must-have:
Full-stack experience preferred; if not full-stack, a genuinely strong backend lean is required
Comfortable owning a feature end to end: scoping it, building it, and deciding what not to build, without a PM pre-slicing the work
Solid Python (we use FastAPI) and TypeScript
EU citizenship (contractual requirement tied to our defense contracts)
Real comfort with ambiguity: the roadmap here shifts with the deployment pipeline
Nice to have:
Experience with PostGIS or other geospatial data work
Experience with LangGraph, LangChain, or orchestrating multi-step LLM workflows
Experience deploying software on-prem or as an appliance rather than pure cloud-native
Prior work in defense, government, or dual-use tech
Competitive package (top 0.1% of compensation in Europe: base + equity)
Paris or London based
Client-site travel is part of the role when a deployment calls for it
Talent screening: 30 min, online. Background and motivation.
Technical test: 60min, online. Skills assessment.
Onsite in Paris: half day. Product demo, a project presentation, a system design exercise, and a re-engineering exercise on an existing codebase.
Roundtable.
Skills Required
- Full-stack experience preferred; otherwise genuinely strong backend experience required
- Ability to own features end to end, including scoping, implementation, and prioritization
- Solid Python experience, including FastAPI
- TypeScript experience
- EU citizenship
- Comfort working with ambiguity and shifting roadmaps
- PostGIS or other geospatial data experience
- LangGraph, LangChain, or multi-step LLM workflow orchestration experience
- On-premise or appliance deployment experience
- Prior defense, government, or dual-use technology experience
What We Do
Comand AI builds AI-native command-and-control software for defence and security operations. Its Prevail workspace ingests multi-source intelligence, analyses terrain and missions, predicts threats, and generates real-time courses of action to accelerate planning while keeping officers in command. Headquartered in Paris with an office in London, the startup is engineered for warfighting and has been deployed with the Bundeswehr.
