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Infrastructure Engineer

Laelaps AI
Zürich, ZH

Postuler rapidement

Détails de l'emploi

100%
Il y a 1 jour

Avantages

Appareils mobiles de fonction

Qualifications

Niveau Doctorat
Google Cloud Platform
AWS
Terraform
GitHub
GitLab
Python

Description complète du poste

Our Mission

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!

The Role

As a 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.

What You'll Work On

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.

Who We're Looking For

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.

Your Background:

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.

What We Offer

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.

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