Platform Engineer
$150,000–$250,000 year
On-siteSan Francisco, California, United States
Job Summary
Own production uptime, latency, provisioning speed, infrastructure cost, and incident response for core platform services by building and maintaining AWS infrastructure using Terraform, Kubernetes/EKS, Helm, Docker, EC2, CodeBuild, ECR, S3, IAM, networking, and secrets management. Design backend systems for scale, implement capacity planning and autoscaling, and establish dashboards, alerts, logs, traces, SLOs, and on-call workflows to ensure rapid failure detection and resolution. Construct reliable CI/CD pipelines, release automation, and environment management to improve developer productivity while reducing production risk through clean, maintainable production code.
Required Qualifications
- 2–4 years of experience owning production cloud infrastructure for a high-availability, user-facing platform, with accountability for uptime, performance, deployment safety, and cost
- Deep hands-on experience with AWS and containerized systems
- Strong familiarity with Terraform, Kubernetes/EKS, Docker, EC2, load balancers, networking, and secrets management
- Track record of building or operating CI/CD, release automation, observability, alerting, and incident response systems
- Strong backend engineering judgment — able to reason about service architecture, APIs, databases, async systems, queues, scaling limits, and production failure modes
- Ability to write production-quality code to automate infrastructure, improve backend services, and build internal tooling
- US-based candidates must be located in San Francisco
- Southeast Asia-based candidates must be located in Singapore
- Candidates based elsewhere — particularly in Europe — may be considered as fully remote independent contractors
- Visa sponsorship is available
Desired Qualifications
- Experience designing systems for bursty workloads, long-running jobs, sandboxed execution, distributed workers, or high-concurrency services
- Background operating infrastructure for data-heavy, ML/AI, workflow, marketplace, developer-tools, or enterprise platforms
- Demonstrated focus on reducing cloud spend through better architecture, autoscaling, workload placement, caching, or cleanup systems
- Experience building internal platforms or developer tools that improve engineering productivity without hiding complexity
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