OpenClaw Orchestration Engineer

Job Description

Requirements
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### Must have:

### - We have at least 2 years of experience in backend engineering, AI automation, or integrating complex systems. - We can build and support production-ready software with clear modular separation, such as distinct services for parsing, logic handling, and reporting. - We are strong in at least two major programming languages, such as Python, JavaScript, Go, or Java, and we have experience with SQL databases. - We have practical experience developing in live, non-simulated environments and managing multi-turn system interactions. - We bring exceptional attention to detail and can deliver concise, high-value technical feedback on intricate system behavior. - It is a plus if we have experience designing multi-stage coordination workflows where data collection leads to reasoned output. - It is a plus if we have hands-on experience connecting agents with live tools such as Supabase, Gmail, and other APIs to solve practical problems. - It is a plus if we are comfortable implementing persistent state and session discovery using MEMORY.md to track agent progress. - It is a plus if we can spot subtle issues such as privacy leaks, authority escalation, or indirect prompt injection.

Responsibilities:
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- We help train advanced generative systems by providing human feedback on AI agent behavior. - We contribute to projects that teach LLMs how to plan, coordinate, and optimize complex real-world workflows. - We evaluate how autonomous agents handle multi-step tasks and provide detailed guidance to improve them. - We analyze system behavior across interactions and identify strengths, weaknesses, and failure points. - We support the development of orchestration-focused solutions for sophisticated architectural use cases. - We apply our technical judgment to refine agent performance in live, production-like environments. - We deliver clear, structured, and high-density feedback to help improve model quality.
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Company:
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We are Outlier, and we help innovative companies improve their AI agents through human feedback. Our work centers on training large language models to act as proactive, multi-step agents that can design, coordinate, and optimize complex real-world architectural workflows. We welcome experienced software developers and orchestration-focused specialists who want to help shape the future of autonomous agents. Our projects are geared toward building the worlds most advanced generative systems.
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