Platform Site Reliability Engineer

Specter•San Francisco, CA

About The Position

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. Soon, we will build robots, trained on top of the data we collect, to take action in these environments as well. 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. We’re hiring a Platform Site Reliability Engineer to own the operational health, reliability, and scalability of the cloud platform behind our connected sensor fleet. This is a high-ownership role at the intersection of site reliability and platform engineering. You’ll operate and improve our Kubernetes-based infrastructure, manage cloud resources through Terraform, strengthen observability and incident response, and build the systems that allow our engineering teams to deploy safely and move quickly. You’ll work primarily across our AWS infrastructure and Kubernetes environments while partnering with application, AI, embedded systems, and fleet teams. You’ll help resolve production issues when they occur—and then improve the platform so they are less likely to happen again.

Requirements

Strong Linux systems knowledge and experience diagnosing production systems.
Hands-on experience operating Kubernetes in production, including networking, storage, resource management, upgrades, and troubleshooting.
Strong experience using Terraform to manage production cloud infrastructure.
Experience with AWS, including IAM, networking, compute, storage, and EKS.
Solid networking fundamentals, including DNS, load balancing, firewalls, VPNs, subnets, and routing.
Experience building operational tooling and automation using Python, Go, Bash, or a similar language.
Strong ownership during incidents and the ability to turn ambiguous failures into lasting improvements.

Nice To Haves

Experience supporting connected devices, edge computing, or on-premises infrastructure alongside cloud systems.
Experience with CI/CD, GitOps, or Kubernetes multi-cluster environments.
Familiarity with cloud and Kubernetes security practices.
Experience reading firmware logs or low-level Rust or C code when debugging across the edge-to-cloud boundary.

Responsibilities

Debug production issues across Kubernetes clusters, Linux systems, AWS infrastructure, networking, and application workloads.
Lead incidents from detection through recovery, coordinating across teams when failures span multiple parts of the system.
Participate in an on-call rotation and follow incidents through to durable fixes.
Build, operate, and improve our Kubernetes platform and the AWS infrastructure supporting it.
Manage production infrastructure with Terraform, including reusable modules, automated validation, and safe change workflows.
Reduce operational toil through automation while improving deployment tooling, CI/CD, and developer workflows.
Design and improve observability into system health, functionality, and performance through logging, metrics, tracing, dashboards, and alerting across Kubernetes workloads and AWS infrastructure.
Define meaningful service-level indicators and objectives, and close telemetry gaps before they become incidents.
Develop runbooks, incident-response procedures, post-incident reviews, and operational readiness standards.

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