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# Software Engineer

- **Company:** CLERA, LLC
- **Location:** Los Angeles, CA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $150,000.0 - $300,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Software as a Service, Programming Tools, PostgreSQL, Next.js, TypeScript, ReactJS, Large Language Models, Build Management, Kubernetes, Information Technology
- **Published:** August 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=54a0d5c2ea259323

## About the Role

We're an early-stage SaaS company building a platform to automate mission-critical integrations for the real economy - specifically focused on supply chain connectivity. We're looking for a Software Engineer with 3-8 years of experience who brings strong technical horsepower, sharp judgment, and a genuine drive to build foundational systems from scratch in a fast-moving environment., * 3-8 years of experience as an individual contributor software engineer.

 * Strong proficiency in TypeScript.
 * Undergraduate degree in Computer Science, Engineering, or a related field.
 * Proven track record of shipping and owning complex software products end-to-end.
 * Hands-on experience building with or using AI agents and/or Large Language Models (LLMs).
 * Experience building platform engineering or infrastructure systems (e.g., runtimes, execution environments).

Nice-to-haves:

 * Prior experience at a developer tools or infrastructure-focused company.
 * Familiarity with any of: React, Bun, Effect-TS, PostgreSQL, Kubernetes, or AWS.
 * Background from a top technical university.

## Description

* Design and build purpose-specific AI coding agents from scratch, tailored for supply chain connectivity use cases.
 * Develop and maintain core infrastructure for hosting and running integrations - effectively a mini-runtime/deployment platform (think Vercel, but purpose-built for our stack).
 * Own core systems end-to-end: from the agent platform to the integrations runtime.
 * Make foundational architectural decisions that will define the platform's future.
 * Establish engineering patterns and best practices that scale with the team and product.
 * Work fluidly across the agentic AI layer and the heavy infrastructure layer of the product.


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