Clera
LLM Engineer
About this role
Join an early-stage Y Combinator-backed AI supply chain startup as a founding LLM engineer, owning end-to-end development of LLM-powered agents that optimize production, logistics, and distribution decisions. You'll design prompts, build multi-step agent workflows, evaluate LLMs for production use, and establish monitoring systems to continuously improve system performance on real-world supply chain data.
What you'll do
- Build and iterate on LLM-powered agents for supply chain decision-making across production, logistics, and distribution
- Design prompts, tool definitions, structured outputs, and multi-step agent workflows handling complex real-world data
- Evaluate and select LLMs based on latency, cost, accuracy, and domain-specific tradeoffs
- Ship LLM features end-to-end from API integration through tested, production-ready systems
- Design and maintain evaluation frameworks for iterating safely on prompts and agent behaviors
- Establish observability, monitoring, and feedback loops to track production accuracy and performance
What they're looking for
- LLM APIs (OpenAI, Anthropic, DeepSeek, Gemini)
- LLM agent design and multi-step workflow architecture
- Prompt engineering and structured output design
- Evaluation pipeline development and LLM benchmarking
- LLM observability and monitoring tools
- HuggingFace ecosystem
- System design and tool definition
- Production-grade feature shipping
Benefits
- Founding team role with high autonomy and ownership
- Visa sponsorship available
- Early-stage Y Combinator-backed startup
- End-to-end LLM system ownership
- Opportunity to work on real supply chain problems at scale
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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 an LLM-powered feature you shipped to production—what were the biggest challenges in moving from prototype to production?
- How do you approach designing and validating prompts and agent workflows when dealing with messy, real-world data?