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Clera

Software Engineer

Los Angeles (Remote)$150k–$300kfulltimemidAdded yesterday

About this role

Early-stage SaaS startup seeks an experienced Software Engineer to design and build AI-powered agents and infrastructure systems for supply chain integration automation. You'll own foundational architecture decisions and work across both agentic AI and complex deployment platforms in a high-ownership environment.

What you'll do

  • Design and build purpose-specific AI coding agents tailored for supply chain connectivity use cases
  • Develop core infrastructure for hosting and running integrations—a custom runtime/deployment platform
  • Own end-to-end core systems from agent platform to integrations runtime
  • Make foundational architectural decisions that define the platform's future direction
  • Establish engineering patterns and best practices that scale with team growth
  • Work fluidly across AI layer and heavy infrastructure components

What they're looking for

  • TypeScript
  • AI agents and Large Language Models (LLMs)
  • Platform engineering and infrastructure systems
  • Runtime and execution environment design
  • End-to-end product ownership
  • React (nice-to-have)
  • Kubernetes or AWS (nice-to-have)
  • PostgreSQL (nice-to-have)

Benefits

  • Salary: $150,000–$300,000 annually
  • Early-stage equity opportunity
  • Direct impact on product direction from day one
  • Shape engineering culture and foundational systems
  • High-ownership role with architectural influence
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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 software system you shipped end-to-end—what were the key architectural decisions?
  • Describe your hands-on experience building or deploying AI agents. What challenges did you face?
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