Founding AI Engineer – Build Agentic Systems That Will Transform Hardware Engineering Techmunity are exclusively hiring a Founding AI Engineer to help build the intelligent core of a new kind of software — one that could transform how robots, rockets, and machines are designed and built. This is a role for deep builders — those who want to go beyond tweaking prompts and instead design entire agentic systems from scratch: how they plan, reason, and execute in real-world engineering environments. The Mission Software has had its Copilot moment. Hardware hasn’t — yet. This AI startup is building a collaborative platform for mechanical, aerospace, and robotics engineers — where AI agents help teams plan, simulate, and run workflows 10x faster. The system is secure, scalable, and built from first principles — orchestrating tools, simulations, and human input through a version-controlled, agent-led interface. The goal: unlock the next generation of physical innovation. The Founders The company is led by second-time founders with elite engineering backgrounds: One was lead engineer at Imperial’s Karman Space Programme, shipping code to satellites and leading reusable rocket development The other built London’s first Hyperloop team from scratch, scaled it to 100 engineers, and went on to launch multiple ventures in deep tech and software They’re backed by SuperSeed, one of Europe’s leading AI VCs — early investors in breakout companies like Magic.dev, AI Build, and others shaping the future of intelligent infrastructure. The Opportunity The company is pre-MVP but moving fast. You’ll be one of the first three engineers, joining just before the Seed round — with full ownership of the AI stack and the freedom to shape how intelligent systems are built from day one. They’re looking for someone who wants to: Build agentic systems with memory, context, and real-world constraints Design abstractions between reasoning, tool execution, and simulation orchestration Define what “usable AI for engineers” actually looks like What You’ll Be Building You’ll work closely with the CTO to architect and implement the intelligence layer of the platform — with real ownership over: Designing and deploying LLM-driven agent systems using LangGraph, LangChain, or similar tools to coordinate tool use, memory, and fallback logic Building orchestration logic for autonomous workflows — handling retries, dependencies, logging, and execution across simulation and design environments Creating custom interfaces between LLMs and domain-specific tools like CAD/CAE systems (e.g. Onshape, Ansys), simulation platforms, and internal APIs Implementing embedding-based retrieval systems, in-context planning, and evaluation pipelines Contributing to agent UX and task planning tools, working closely with product and frontend engineers Integrating deeply with a backend built in Python and Rust, deployed on Docker/Kubernetes (AWS) What You’ll Need 1–3 years of professional software engineering experience — ideally in fast-moving, early-stage environments Strong Python skills, with a track record of building or deploying LLM-based systems in production Hands-on experience with frameworks like LangChain, LangGraph, or custom-built agent orchestration setups Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, etc.), embedding stores, retrieval pipelines (e.g. Weaviate, Pinecone), and eval tooling Comfort building and testing AI workflows that interact with external APIs, file systems, simulations, and toolchains Bonus: interest or experience in robotics, mechanical/aerospace workflows, or simulation environments A history of high-agency contributions — student teams, startup side projects, open source, or technical competitions Logistics & Perks Hybrid: 3–4 days/week in their Hoxton office (London) Competitive salary (we're talking top 0.01% of the market here) founding-level equity Ownership from day one: direct line to the CTO, influence on product and architecture A chance to define a new category of applied AI and own a piece of what comes next If that excites you, apply now or reach out for a conversation: reuben@techmunity.io