Founding Software Engineer

CLERA, LLC
San Francisco, CA, United States
2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

A/B Testing Artificial Intelligence Amazon Web Services PostgreSQL Next.js Systems Integration TypeScript Google Cloud ReactJS Large Language Models

Job description

We’re building an AI motion design platform and this is our founding engineering hire. You’ll work closely with the founders to shape the technical foundation, own end-to-end development, and help scale a product designed to empower millions of users with fast, high-quality animations., * Partner with the founders to deliver user-centric product solutions from concept to production.

  • Own end-to-end development of full-stack features with scalable architecture design.
  • Build and optimize agentic LLM systems incorporating tool-calling, multi-step reasoning, and MCP protocols.
  • Design comprehensive LLM evaluation frameworks with automated benchmarks, human-in-the-loop validation, and A/B testing.
  • Optimize LLM inference performance, cost efficiency, and latency across multiple model architectures.
  • Develop a high-performance motion graphics engine.
  • Drive architectural decisions that support scalable growth to millions of users.

Requirements

Do you have experience in Validation design?, * Strong CS fundamentals.

  • Hands-on experience building or integrating large language models (LLMs), tool-calling, multi-step reasoning, and MCP protocols.
  • Experience designing and implementing LLM evaluation frameworks with automated benchmarks, human-in-the-loop validation, and A/B testing.
  • Demonstrated ability to deliver end-to-end full-stack features with scalable architecture.
  • Startup/early-stage company experience with an ownership mindset.
  • Proficiency with the full tech stack: TypeScript, React.js, Next.js, PostgreSQL, GCP, AWS.
  • Proficiency in optimizing LLM inference performance, cost efficiency, and latency across multiple model architectures.

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