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Clera

Platform Engineer

San Francisco$150k–$250kfulltimemidAdded today

About this role

Join a lean engineering team to design and operate AWS-based platform infrastructure at scale. You'll own production reliability, CI/CD automation, observability, and cost efficiency for a high-availability system while writing clean infrastructure-as-code and backend tooling.

What you'll do

  • Own production uptime, latency, provisioning, and incident response for core platform services
  • Build and maintain AWS infrastructure using Terraform, Kubernetes/EKS, Docker, and related services
  • Design backend systems for scale including capacity planning, autoscaling, queueing, and rollback strategies
  • Define and improve monitoring, alerting, SLOs, runbooks, and on-call workflows
  • Build reliable CI/CD pipelines and release automation to improve developer productivity
  • Write maintainable code to automate systems and create internal developer tooling

What they're looking for

  • AWS (EC2, EKS, CodeBuild, ECR, S3, IAM, networking, secrets management)
  • Terraform and Infrastructure as Code
  • Kubernetes and container orchestration
  • Docker and containerization
  • CI/CD pipeline design and deployment automation
  • Observability, monitoring, alerting, and SLO definition
  • Backend systems design and distributed systems
  • Production-grade backend development in any language

Benefits

  • Salary range: $150,000–$250,000 USD annually
  • Visa sponsorship available
  • On-site opportunity in San Francisco
  • Remote contractor option for non-US candidates
  • Opportunity to work with a tight-knit team of ~15 engineers
  • Direct impact on platform reliability and developer experience
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Walk us through a time you owned production uptime and incident response — what was the failure mode and how did you respond?
  • Describe your experience with Terraform and Kubernetes — what complex infrastructure have you provisioned or troubleshot?
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