At Laelaps AI, we believe robotics is entering a transformative decade, much like the arrival of the internet. Advances in AI, cloud computing, and hardware are reshaping what autonomous systems can do. Our mission is to build the intelligent software that powers physical security in the real world - enabling robots and sensors to handle dangerous and critical tasks that humans shouldn't have to. By engineering the orchestration layer for intelligent security, we aim to create a world that is safer, more secure, and more resilient.
We're a strong founding team based in Zurich, backed by visionary investors and advisors. We are engineering the future of security today!
As a Forward Deployed Engineer, you own our customer deployments end to end. Our system runs on-prem at industrial facilities, critical infrastructure, and military sites, integrated with the cameras, networks, and robots already in place. You survey the site, plan the deployment, install and integrate the system, tune it to the site's conditions, and hand it over to operators who will rely on it daily.
You are also the technical face of Laelaps on site. You work with security operators to understand how they actually work and where the bottlenecks are, align with their leadership on what success looks like, and translate what you learn into configuration, code, and product priorities. Early deployments you run alongside the founders; over time you own sites and accounts independently.
Expect roughly half your time at customer sites in Switzerland and Europe, the rest in Zurich turning field lessons into tooling and automation that make each deployment faster than the last. This is an engineering role with a customer in the room, not a support or services role.
Deployments end to end: site surveys, network and hardware planning, installation, camera and VMS integration, commissioning, and handover.
On-prem infrastructure: install and manage our stack on edge hardware (NVIDIA DGX Spark, Jetson Thor class devices) inside customer networks, often air-gapped or heavily restricted.
Integrations: connect existing cameras, sensors, VMS platforms, and robots into one coordinated system, and write the glue code where no integration exists yet.
System tuning: calibrate detection and tracking to each site's terrain, lighting, and threat profile until the system performs in the field like it does in the demo.
Pilots to production: make POCs succeed technically, because pilots that work become contracts.
Customer understanding: sit with operators, interview stakeholders from the control room to the leadership floor, and map the real problems and bottlenecks behind the stated requirements.
Customer trust: train operators, respond fast when something breaks, and be the engineer customers ask for by name.
The deployment playbook: turn every hard-won lesson into runbooks, tooling, and automation that compound.
Product feedback: bring real field signal back to the core engineering team and shape the roadmap with it.
We are looking for an engineer who runs toward the messy parts, with the EQ to match the IQ. You are as comfortable in a server room or on a windswept perimeter as you are in a terminal, and just as comfortable in a conversation. You can spend a shift with a security operator and earn enough trust that they tell you what actually goes wrong at 3 a.m., then brief a head of security or a site director in their language, not yours. You listen more than you pitch, you read the room, and you switch registers between the guard house and the boardroom without breaking stride. You debug across the whole stack without ceremony: is it the camera, the network, the driver, the model, or the config? Above all, you take personal ownership of the outcome: the deployment works because you made it work, and the customer trusts us because you earned it.
3+ years of software engineering experience, with strong Python and solid Linux fundamentals.
High EQ, demonstrated: you have worked directly with end users or customers, uncovered what they actually needed, and navigated stakeholders from frontline staff to senior leadership.
Experience deploying and operating software on-prem or at the edge (Docker required; GPU inference experience a strong plus).
Customer-facing composure: you can run a technical session with a client and hold your own when things go sideways.
Fluent German and good English. Our sites and their operators run in German; the team runs in English.
Willingness to travel regularly to customer sites across Switzerland and Europe, with some multi-day on-site stints.
Based in or willing to relocate to Zurich.
Citizenship of Switzerland, an EU/EFTA member state, or a NATO member state, and eligibility for security clearance where customer sites require it.
Real networking competence: VLANs, firewalls, routing, VPNs, and debugging connectivity in networks you do not control.
Hands-on comfort with hardware: you have racked servers, flashed devices, crimped a cable, or built systems that touch the physical world.
Experience with cameras, VMS platforms (Milestone, Genetec, or similar), ONVIF/RTSP, or the physical security industry.
Computer vision or ML deployment experience, especially optimising inference on edge GPUs.
Robotics experience: ROS2, robot integration, or fleet operations.
Experience in defence, government, or other regulated environments.
French, Italian, or another European language on top of German and English.
Startup experience, ideally somewhere you were handed a hard problem and a deadline instead of a spec.
Ownership: you are the commercial function, and first in line to build and lead the team you help hire.
Mission: autonomous security that keeps people and critical sites safe, including in defence.
Career path: a ground-floor seat with real runway. Prove your value and you will not have barriers to grow.
Team: work directly with PhD-level co-founders in AI, Robotics, and Physics, alongside a strong (and fun) founding team.
Compensation: Competitive equity/salary package
Culture: a small, international founding team that is serious about building but does not take itself too seriously.
