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Serval

Software Engineer, Infrastructure

San Francisco$200k–$325kfulltimemidAdded 1 month ago

About this role

Serval, an AI-native automation platform backed by Sequoia Capital, seeks an Infrastructure Software Engineer to design and operate distributed systems powering enterprise workflow automation. You'll build cloud infrastructure, enable self-hosted deployments for enterprise customers, and provide technical support for on-premises installations.

What you'll do

  • Design and operate large-scale distributed systems for AI agents and workflow orchestration
  • Write and maintain Terraform modules for AWS, GCP, and Azure infrastructure provisioning
  • Build deployment packages and installation scripts enabling customer self-hosted deployments
  • Provide technical guidance and troubleshooting support to enterprise customers
  • Ensure production system reliability through monitoring, alerting, and incident response
  • Optimize system performance across compute, storage, networking, and database layers

What they're looking for

  • Distributed systems design and operations
  • Terraform and infrastructure-as-code
  • Cloud platforms (AWS, GCP, or Azure)
  • Python or Go programming
  • Kubernetes and containerization (Docker)
  • Monitoring and logging tools (Datadog, Prometheus, Grafana)
  • Networking and database knowledge
  • Customer-facing technical support
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Serval

Serval builds an AI-native enterprise automation platform that enables intelligent workflow automation for sophisticated IT and security buyers. The company is hiring for technical pre-sales, infrastructure engineering, and security leadership roles to scale its cloud and self-hosted deployments while establishing comprehensive security foundations across its multi-tenant platform.

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Likely interview questions

  • Walk us through your experience building and operating large-scale distributed systems in production. What was the most complex scaling challenge you've faced, and how did you solve it?
  • Describe your experience with Terraform—how have you structured modules for multi-environment deployments, and what patterns have you found most effective for maintainability?