Infrastructure Engineer
AI-Powered Physical Security Robotics Company · Zürich, Switzerland ·
- Seniority
- Senior
- Employment
- Full time
- Category
- Devops
- Experience
- 4+ years
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 an Infrastructure Engineer, you'll build the cloud platform connecting our robot fleet to operator intelligence. You'll own cloud setup, deployment pipelines, CI/CD, container orchestration, and the secure networking that lets the engineering team ship code from laptop to robot reliably, securely, and at scale.
This is a critical early-stage hire. The systems you build will define how the company ships software for years. You'll work across the stack: infrastructure-as-code, container orchestration, secure connectivity, observability, edge fleet management, and developer experience. Because we deploy on-prem to security-sensitive customers, you'll care as much about hardened, self-contained deployments as you do about speed. You'll move fast where it matters and build things to last where it counts.
Cloud infrastructure: AWS or GCP foundations, networking, security, IAM, cost controls
Secure networking: VPNs, certificate and PKI management, TLS, and hardened connectivity between cloud, operators, and robots in the field
CI/CD pipelines: fast, reliable, repeatable builds and deploys for both cloud services and on-robot software
Container orchestration and runtime: Kubernetes and lightweight distributions (K3s) for edge and on-prem, image build pipelines, secrets management
Edge and fleet management: OTA updates, configuration management, telemetry, secure connectivity to robots in the field
Observability: logging, metrics, tracing, dashboards, and alerting across cloud and edge (Grafana, Prometheus, and similar)
Developer experience: local environments, testing infrastructure, internal tooling that removes friction for the rest of the team
Security and compliance: baseline hardening, secrets, audit trails, and the foundations needed for enterprise and government customer trust
We're looking for a senior infrastructure engineer who has built cloud infrastructure at startup scale, knows when to keep things simple and when to invest in durable foundations. You write code, you operate systems, you're comfortable owning the network and security layer, and you care about making the engineering team around you faster.
4+ years in platform engineering, DevOps, SRE, or infrastructure roles
Deep experience with at least one major cloud (AWS, GCP, or Azure)
Strong with Kubernetes (including lightweight distributions like K3s) and infrastructure-as-code (Terraform, Pulumi)
Solid networking and security fundamentals: VPNs, TLS, certificate and PKI management, firewalls
Solid CI/CD chops: GitHub Actions, GitLab CI, or similar
Comfortable writing code in Python, Go, or similar systems languages
Track record of building developer-facing platforms that engineers actually liked using
Nice to have:
Experience deploying software to edge devices or robot fleets (OTA, A/B updates, rollback)
Experience with on-prem or air-gapped environments
Background in security-sensitive environments: enterprise, defense, fintech, healthcare
Familiarity with observability stacks (Grafana, Prometheus, Datadog, OpenTelemetry)
Experience supporting ML workloads: training infrastructure, model serving, GPU orchestration
Mission: Build the foundation models that decide how robots see, reason, and act in the real world. Research with deployment, not papers without impact.
Autonomy: Real independence on what to train, how to evaluate, and how to ship.
Compute: Access to the compute and field data you need to do serious work.
Team: Work alongside PhD-level co-founders in AI, Robotics, and Physics, plus a strong founding engineering team.
Location: In-person in Zürich, Switzerland, with remote considered for exceptional candidates. Visa and relocation support available.
Culture: Small, international founding team that's serious about building, but doesn't take itself too seriously. Curiosity and quirks welcome.