Clera
Founding Engineer
About this role
Join an early-stage AI/ML startup as the first full-time engineer outside the founding team, owning the complete system that detects failures in agent conversations and auto-generates fixes via pull requests. You'll architect core infrastructure, establish engineering standards, and work directly with customers to ship production-grade detection, patching, and verification systems.
What you'll do
- Own end-to-end pipeline from failure detection through patch generation, verification, and customer deployment
- Design and maintain trust safeguards including reproduction logic and guardrails to prevent faulty PRs reaching customer repos
- Independently scope and ship solutions directly from customer problems without waiting for specifications
- Engage directly with customers to diagnose issues, analyze traces, and surface problems before escalation
- Make architectural decisions on schemas, service boundaries, and correctness-versus-speed tradeoffs
- Define engineering culture including testing standards, on-call practices, and release criteria from the ground up
What they're looking for
- TypeScript (full-stack: frontend, backends, services)
- Data pipeline design and optimization with cost awareness
- AI agent development and production operation
- System architecture and long-term design decisions
- Observability, monitoring, and production debugging
- Product thinking and ambiguous problem-solving
- High-volume data handling (cost-per-event thinking)
- PR automation or code quality tooling (bonus)
Benefits
- Ownership of entire technical direction and engineering culture
- Direct customer interaction and influence on product decisions
- Equity opportunity as founding engineer
- Work on AI/ML-driven automation at an early-stage startup
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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.
View all jobs at CleraLikely interview questions
- Tell us about a time you owned an end-to-end system from design through production—what was your decision-making process for architectural tradeoffs?
- How do you approach building high-volume data pipelines with cost constraints, and can you walk us through a specific example?