Clera
Founding Engineer
About this role
A seed-stage AI startup seeks a Founding Engineer to architect and deploy AI agent systems for defense and medical device engineering firms. You'll own the entire technical stack, ship production workflows into customer programs, and build evaluation loops that improve system performance from real-world feedback.
What you'll do
- Design and build core system architecture integrating AI agents with CAD, CAE, and PLM tooling with enterprise security requirements
- Own end-to-end engineering: architecture, production delivery, observability, evaluation suites, regression testing, and on-call operations
- Ship first production AI workflow into live customer program and iterate on real-world failure modes
- Build evaluation and training loops including reinforcement learning grounded in real physics
- Visit customer sites to understand system failures and translate learnings into durable platform capabilities
- Expand platform across multiple partner companies while hiring and mentoring a small engineering team
What they're looking for
- LLM agent workflows and tool integration in production
- Python and backend/ML systems engineering
- Observability, evaluation suites, regression testing, and on-call operations
- Agent orchestration architecture and design
- Feedback loops and evaluation pipelines for AI model improvement
- Customer environment deployment and real-world iteration
- Technical communication with domain experts and non-technical stakeholders
- Production systems reliability and troubleshooting
Benefits
- Founding equity package
- Opportunity to build and lead engineering from day one
- Work directly with Co-Founder and CTO
- Set technical standards for future hires
- Direct customer interaction and impact on real engineering programs
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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 production LLM agent system you shipped. What were the failure modes and how did you design your evaluation suite to catch them?
- Describe your experience building feedback loops for AI model improvement. How did you prioritize which failures to address first?