Clera
Founding Engineer
About this role
Join an early-stage AI company as the founding engineer to build systems that accelerate hardware design by integrating AI agents with CAD, CAE, and PLM tools. You'll own the full technical stack, deploy production workflows for defense and medical customers, and directly shape the platform alongside the co-founder and CTO.
What you'll do
- Design and build core architecture integrating AI agents with CAD/CAE/PLM tools while meeting defense and medical security requirements
- Own end-to-end production engineering: architecture, deployment, observability, testing, and on-call operations
- Ship and iterate on production AI workflows with real customers, collecting feedback from live usage
- Build evaluation and training loops using simulation data, test cases, and reinforcement learning grounded in physics
- Partner with customer engineers to identify system failures and convert learnings into platform improvements
- Scale platform across multiple companies and mentor the growing engineering team
What they're looking for
- Python and backend systems engineering
- LLM agent workflows and tool calling patterns
- Production ML systems and observability
- Evaluation frameworks and regression testing
- Reinforcement learning and fine-tuning strategies
- CAD, CAE, EDA, or PLM tools (preferred)
- On-call operations and failure handling
- Domain knowledge in robotics or autonomous systems (preferred)
Benefits
- Founding engineer equity and impact at early-stage AI company
- Direct partnership with co-founder and CTO
- Hands-on work with defense and medical device leaders
- Opportunity to shape product roadmap and team growth
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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 production AI system you deployed—what was the toughest part of getting it to handle failures gracefully?
- How have you designed and validated evaluation suites for LLM-based workflows? When would you choose RL over fine-tuning?