Infrastructure Engineer

About the role

Laelaps builds the intelligent software that powers physical security in the real world, letting robots and sensors handle dangerous and critical tasks people shouldn't have to. As our Infrastructure Engineer, you'll build the platform that connects our robot fleet to operator intelligence, owning cloud, CI/CD, container orchestration, and the secure networking that lets the team ship code from laptop to robot reliably and at scale.

This is a critical early-stage hire, and the systems you build will define how the company ships software for years. Because we deploy on-prem to security-sensitive customers, success means deployments that are fast to ship, hardened, self-contained, and observable in the field. You'll work across the stack with the founding engineering team and make every engineer around you faster.

Responsibilities

• Build and operate cloud infrastructure: AWS or GCP foundations, networking, security, IAM, and cost controls.
• Own secure networking: VPNs, certificate and PKI management, TLS, and hardened connectivity between cloud, operators, and robots in the field.
• Build fast, reliable, repeatable CI/CD pipelines for both cloud services and on-robot software.
• Manage container orchestration and runtime: Kubernetes and lightweight distributions (K3s) for edge and on-prem, image build pipelines, and secrets management.
• Run edge and fleet management: OTA updates, configuration management, telemetry, and secure connectivity to robots in the field.
• Build observability across cloud and edge: logging, metrics, tracing, dashboards, and alerting (Grafana, Prometheus, and similar).
• Improve developer experience through local environments, testing infrastructure, and internal tooling that removes friction for the team.
• Establish security and compliance foundations: baseline hardening, secrets, and audit trails for enterprise and government customer trust.

Qualifications

Required:

• 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 experience: GitHub Actions, GitLab CI, or similar.
• Comfortable writing code in Python, Go, or a similar systems language.
• Track record of building developer-facing platforms that engineers liked using.

Preferred:

• 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, defence, fintech, or healthcare.
• Familiarity with observability stacks (Grafana, Prometheus, Datadog, OpenTelemetry).
• Experience supporting ML workloads: training infrastructure, model serving, GPU orchestration.