Laelaps AI Logo

Laelaps AI

Software Engineer, Infrastructure

Posted 22 Days Ago
Be an Early Applicant
In-Office
Zürich
Mid level
In-Office
Zürich
Mid level
Build and operate cloud and edge infrastructure connecting robot fleets to operator systems. Responsibilities include cloud networking and IAM, secure VPN and PKI connectivity, CI/CD, Kubernetes and K3s orchestration, infrastructure as code, fleet management, observability, developer tooling, and security hardening. The role supports cloud, on-premises, and potentially air-gapped deployments, with ownership of durable infrastructure foundations and developer experience.
The summary above was generated by AI
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 Software Engineer on Infrastructure, 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 able to ship products and deliver project end-to-end.

  • 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: International founding team that is serious about building but does not take itself too seriously.

Similar Jobs

8 Days Ago
In-Office
San Francisco, CA, USA
Senior level
Senior level
Artificial Intelligence • Robotics • Software
Build and own infrastructure platforms, tooling, APIs, SDKs, and customer-facing applications that support large-scale humanoid robot deployments. Lead projects from design through rollout, shape architecture across teams, operate reliable backend systems, and improve testing, documentation, and engineering practices. Partner with research, robotics, and deployment teams while advancing AI-assisted development tooling.
Top Skills: APIsC++Ci/CdClaude CodeCloud InfrastructureCodexDatabasesDistributed ComputingDistributed SystemsDockerGitGitGoJavaScriptMessage QueuesNetworkingOpencodePub/SubPythonRustTypescript
2 Months Ago
In-Office or Remote
Senior level
Senior level
Artificial Intelligence • Information Technology • Consulting
Build and maintain services and tooling to automate and secure network lifecycle across data centers. Implement CI/CD, staged rollouts, drift detection, observability pipelines, and APIs that integrate network source-of-truth with the cloud platform. Collaborate with network engineers and SREs to turn operational pain into production-grade automation and tooling.
Top Skills: APIsCi/CdDpdkEbpfGoInfrastructure As CodeKernel NetworkingLogsPythonTelemetry (MetricsTraces)Xdp
2 Months Ago
Remote or Hybrid
San Francisco, CA, USA
Senior level
Senior level
Cloud • Productivity • Software • Infrastructure as a Service (IaaS)
Build and maintain the control planes, automation, and observability for a global fleet of machines. Develop production-quality Go services for provisioning, health checks, upgrades, and incident remediation. Architect high-throughput, low-latency networking, improve utilization and power-to-performance, and collaborate with product and platform teams on storage-aware scheduling and developer-facing features.
Top Skills: AnsibleGoKubernetesTerraform

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account