Infrastructure & Automation Engineer

Company Background
Specter's mission is to help automate the physical world.

Today, we build video sensors with state-of-the-art AI agents that answer any question, anywhere in their environments. Our systems can automatically detect and reason about any physical activity captured on camera, from security incidents (e.g. perimeter intrusion, theft, LPR), to safety monitoring (e.g. PPE detection, injured people), to operational efficiency (e.g. material tracking, congestion monitoring). We offer both long range wireless (1km range) and wired sensor variants to suit any deployment.

Our co-founders Xerxes and Philip are passionate about empowering our partners in the fast approaching world of physical AI and robotics. We are a small, fast growing team who hail from Anduril, Tesla, Uber, and the U.S. Special Forces.

The Role
We’re hiring an Infrastructure & Automation Engineer to build the internal infrastructure that lets us develop, test, and deploy across our sensor fleet at speed. As we add hardware variants and scale the fleet, validating new hardware and pushing software to the field are becoming bottlenecks — this role exists to solve both with automation.

This is the proactive side of fleet operations: the test infrastructure, deploy orchestration, and tooling that prevent fires before they start. Early on, that means owning the release pipeline end-to-end — cutting dev and production releases, validating them against the dev fleet, and making rollouts automated, observable, and reversible.

Responsibilities:

Release & Fleet Validation Pipeline — Primary

• Own how releases get cut, versioned, and promoted — dev vs. production — with automated regression gates.

• Own the CI/CD plumbing for firmware and software builds: the pipelines, infrastructure, and results tracking every build and HW rev flows through.

• Build fleet-side validation: bake periods on the dev fleet and observational checks (health metrics, regressions vs. baseline, tail latencies) that qualify a release for production.

• Own the CI and orchestration rails that validation suites plug into — validation engineering owns the tests and hermetic environments (HIL, device farms, SIL).

• Keep the internal dev and test fleet healthy and available.

Deploy & Fleet Orchestration

• Own the deploy methodology across the fleet: make OTA / software rollouts automated, observable, and rollback-capable so a bad push is a non-event, not an incident.

• Build the tooling and pre-deployment checks that catch problems before they reach devices.

• Improve tracking and visibility for deploys and fleet state — what version is where, what succeeded, what needs attention.

Internal Tooling & Automation

• Automate toil relentlessly — turn repetitive work like deployment tickets, debug handoffs, and fleet checks into code.

• Build internal tooling that makes the rest of engineering faster, and maintain it as real software — versioned, tested, documented.

• Instrument the systems you build so the team can make data-driven decisions about test and deploy reliability.

Qualifications

• Strong scripting/programming for operational tooling — Python, Go, or Bash — and the instinct to automate rather than repeat.

• Hands-on CI/CD experience: building and maintaining pipelines, not just consuming them (GitHub Actions, GitLab CI, Jenkins, or similar).

• Solid Linux fundamentals — comfortable working over SSH in real environments, not just dev.

• Infrastructure-as-code and config management familiarity (Terraform, Ansible, or equivalent).

• Containerization experience (Docker; Kubernetes a plus).

• Networking fundamentals: DNS, firewalls, VPNs, subnets, secure remote access.

• Nice to have: experience across the hardware-software boundary — comfortable reasoning about firmware, embedded systems, and what’s happening below the OS.

• Cloud experience (AWS infrastructure, IAM, networking, observability tooling) is a plus for the deploy and tracking side.

• Bias toward shipping: you’d rather land a working tool today and iterate than design the perfect system for three months.