Clera
Forward Deployed Research Engineer
About this role
Join a fast-growing AI infrastructure company as a Forward Deployed Research Engineer to solve urgent, ambiguous technical challenges for frontier AI labs and data vendors. You'll own end-to-end deployments, build critical tools and pipelines, and transform firefighting into reusable solutions with immediate impact.
What you'll do
- Diagnose and resolve ambiguous technical problems independently and quickly
- Own technical deployment requests from AI labs and vendors through completion
- Build tools and one-off pipelines to solve urgent customer and partner problems
- Clarify under-specified asks and identify actual technical requirements
- Coordinate with research and go-to-market teams to unblock deployments
- Document recurring issues and automate manual work into reusable processes
What they're looking for
- Python programming
- Docker containerization
- Linux system administration
- Reinforcement learning benchmarks and evaluations
- Technical debugging across code, data, and environments
- Deployment and DevOps practices
- Data pipeline development
- Cross-functional technical communication
Benefits
- Visa sponsorship available
- On-site role in San Francisco with office presence in Singapore
- Work on frontier AI and infrastructure problems
- Autonomy and ownership of high-impact technical challenges
- Early-stage startup environment with direct impact
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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 debugged a production issue across code, data, and infrastructure—what was your process and how did you prioritize?
- Describe an example where you took a vague or under-specified customer request and turned it into a concrete technical solution. How did you clarify what was actually needed?