Clera
Founding Engineer
About this role
Join an early-stage AI/ML startup as the first full-time engineer outside the founding team. You'll own the complete system for detecting agent failures and generating fixes, from data ingestion to customer-facing verification, while establishing the engineering culture for future hires.
What you'll do
- Ship end-to-end features from failure detection through patch generation and verification into production
- Own the trust and safety layer including reproduction logic, guardrails, and checks to prevent bad deployments
- Work directly with customers to understand failures, read traces, and prioritize solutions without formal specs
- Make architectural decisions on schema design, service boundaries, and performance tradeoffs that scale
- Define engineering standards including testing practices, on-call procedures, and deployment criteria
- Operate across the full stack including detection quality, data pipelines, and review UI
What they're looking for
- TypeScript across full stack (frontend and backend services)
- Production AI/ML system experience with understanding of agent failure modes
- Data pipeline design and high-volume event processing with cost optimization
- System design and architectural decision-making
- Production observability, monitoring, and debugging
- Ability to work autonomously on ambiguous customer problems
- Strong product sense and customer collaboration
Benefits
- Visa sponsorship available
- Shape engineering culture and practices from the ground up
- Work on impactful AI/ML infrastructure problems
- Direct customer interaction and influence on product direction
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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
- Walk us through a time you shipped a production feature end-to-end without detailed specifications—how did you approach the ambiguity?
- Describe your experience building or operating AI agents in production. What were the most common failure modes you encountered?