Application Software Engineer

ABOUT US Harmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces. Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected. About the Role As a Software Test & Validation Engineer, you build the systems that let us trust our drones' software before it ever flies a mission. You design the automated tests and pipelines that put our flight software through its paces, from pure simulation (SITL) to hardware-in-the-loop (HITL), and turn the results into clear signal for the engineering teams. Our validation team is scaling fast, from testing a handful of drones to testing them by the hundred, and you are how that scale becomes possible. Your main instrument is the SITL/HITL simulation environment built by our tooling team. A big part of the job is to use it to its full potential and to help improve it continuously: it's recent and not yet fully representative of reality, so your feedback and contributions are what will make it a trustworthy test bench. On top of that, new systems to validate arrive on a regular basis, so you'll repeatedly stand up test coverage for platforms you're seeing for the first time. This is a broad role, and we're deliberately hiring for a range of profiles rather than a single narrow one. We're looking for engineers with scope beyond pure software, system-level thinking, a feel for architecture, a statistical approach to noisy data, and some physical intuition. Depending on your strengths, you might focus on test-scenario design and coverage, on the automation and CI pipeline that runs tests on every build, on capturing and replaying flight telemetry, or on deepening the simulation itself. Tell us in your application where you fit best. What you'll do (the mix depends on your profile, you won't do all of it) * Test design & content: Define the scenarios that catch real bugs, decide what to measure, and turn noisy flight metrics into stable, meaningful pass/fail and regression signals. * Drive and improve the SITL/HITL environment: Use the tooling team's simulation bench as your primary test instrument, push it hard, and feed back concrete improvements to make it more representative, models, scenarios, missing capabilities. * Automation & tooling: Write clean Python tools to load, parse and analyse test outputs, detect regressions, and produce reports the engineering teams act on. * CI/CD integration: Integrate simulation and hardware tests into the continuous-integration pipeline so every new build is validated automatically, fast, and reproducibly. * Onboard new systems: As new platforms arrive, build the test scenarios, metrics and coverage to validate them, often starting from scratch. * Telemetry & replay: Capture flight and test telemetry and make it replayable and analysable, so an issue seen once can be reproduced and understood. What we're looking for (we don't expect every point, show us your strengths) * Background in software engineering, embedded systems, mechatronics, aerospace, or a closely related field. * Strong Python for test tooling and automation (C++ is a plus, and more important for some of these profiles than others). * Scope beyond pure coding: system-level thinking, an ability to grasp a whole architecture, a statistical mindset for noisy test data, and enough physical intuition to reason about flight behaviour. * Some combination of: test-scenario/framework design; CI/CD and DevOps tooling (Docker, Jenkins/GitLab CI, Git, Linux); simulation (SITL/HITL); or telemetry capture and analysis. * A validation mindset: rigor, attention to edge cases, and healthy scepticism about what "passing" really means. * Clear communication and ownership, you'll work hand in hand with the flight-software, simulation/tooling and hardware teams. * Bonus: a background in drones or robotics; experience with statistical analysis of noisy test data. We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

Adaptyv is building an automated lab that lets AI agents run biology experiments. We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world. We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today. Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development. We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation. ABOUT THE ROLE We build our lab automation ourselves. Instead of buying turnkey systems and running them through a vendor's GUI, we reverse-engineer instruments, control them with open-source Python tooling like PyLabRobot and PyHamilton, and build the software and hardware to turn a pile of instruments into work cells that run biology around the clock. We're looking for a Lab Automation Engineer to help design, build, and run these systems. This is a broad role: on any given week you might be writing a driver for a new instrument, getting a liquid handler and a robot arm to hand off cleanly, or debugging why an overnight run stalled. We care far more about range, ability, and drive than years on any one platform. WHAT YOU'LL DO * Control lab instruments — liquid handlers, robot arms, plate readers, incubators, analytical devices — programmatically in Python, ideally with PyLabRobot / PyHamilton, rather than locking workflows into proprietary software. * Build and integrate work cells: get multiple instruments working together as one orchestrated unit that runs unattended. * Bring new instruments online by reverse-engineering their control protocols and building drivers that expose them to the rest of the stack. * Write the software glue — drivers, integrations, small services — that connects hardware to our platform (mostly Python, with some TypeScript). * Partner with biologists to turn new assays into reliable automated workflows, then keep them running: diagnosing and fixing the mechanical, electrical, and software failures that come with 24/7 production. * Push throughput and reliability up continuously — better error recovery, smarter scheduling, sturdier hardware. WHAT WE'RE LOOKING FOR * Maker and hacker attitude. You like taking systems apart, figuring out how they work, and building the thing that makes them work better. You'd rather script an instrument than click through it. * Strong software engineering skills. You write real Python and can structure code others can maintain — drivers, integrations, services — not just throwaway scripts. You'll pick up TypeScript where needed. * Lab automation experience. Hands-on with PyHamilton, PyLabRobot, Opentrons, or similar tooling is a strong plus. Direct experience automating instruments and workflows matters more than the specific platform. * Self-starter and independent. You see what needs building and build it. You don't wait for a spec, and you don't need a vendor training course to get going. * AI-native builder. It's 2026 — you build with coding agents like Claude Code as a default, and you have sharp judgment about what they produce. * Hardware comfort is a plus. Electronics, microcontrollers, 3D printing, CAD, or fabrication experience all help, but they're not required if your software and automation skills are strong. * Debugging instinct. When something fails mid-run, you reason across software, firmware, electronics, and mechanics to find the cause and fix it. Biology background not required — but you should be excited that the robots run real experiments. DETAILS * Location: Lausanne, Switzerland (on-site — you're building physical systems) * Type: Full time * Start date: ASAP We review applications on a rolling basis. Application deadline We are reviewing applicants on a rolling basis.