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Clera

Founding Cloud Infrastructure Engineer

remote (Remote)fulltimemidAdded today

About this role

A seed-stage enterprise AI startup is seeking a Founding Cloud Infrastructure Engineer to design and build cloud infrastructure from scratch for a semantic AI platform serving regulated industries. You'll own the full infrastructure lifecycle and make foundational architectural decisions that shape the company's long-term operations.

What you'll do

  • Design and build production-grade cloud infrastructure for an enterprise AI semantic platform
  • Own infrastructure lifecycle from architecture through deployment, scaling, and reliability
  • Make foundational architectural choices that define company operations long-term
  • Establish infrastructure best practices, standards, and tooling in a greenfield environment
  • Build and maintain CI/CD pipelines and deployment automation systems
  • Design and implement database infrastructure at scale for both relational and NoSQL systems

What they're looking for

  • Cloud infrastructure design and deployment (AWS, GCP, or Azure)
  • Infrastructure-as-code tools (Terraform, CloudFormation, or Pulumi)
  • Kubernetes and container orchestration in production
  • CI/CD pipeline design and deployment automation
  • Monitoring, observability, and logging tools (Prometheus, ELK, Datadog, New Relic)
  • Database infrastructure architecture (relational and NoSQL)
  • Infrastructure security, networking, and access control
  • Data infrastructure and AI/ML platform systems (preferred)
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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 complex cloud infrastructure architecture you've designed from scratch — what were your key design decisions and why?
  • Describe your experience building and operating Kubernetes in production — what challenges did you face and how did you solve them?
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