Autonomous Agent Engineer

Job Description

Requirements
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### Must have:

### - We bring at least 2 years of experience in backend engineering, AI automation, or integrating complex systems. - We have demonstrated success building and supporting production-ready software with clear modular boundaries, such as separate services for parsing, business logic, and reporting. - We are proficient in at least two major programming languages, such as Python, JavaScript, Go, or Java, and we have hands-on experience with SQL databases. - We have practical experience developing in live, non-simulated environments and managing multi-step system interactions. - We have excellent attention to detail and can deliver precise, high-density technical feedback on sophisticated system behavior. - We have experience designing multi-stage coordination workflows where data gathering leads to informed outputs. - We have familiarity with connecting agents to live tools and APIs, such as Supabase and Gmail, to address real-world use cases. - We are comfortable implementing persistent state and session tracking using MEMORY.md to monitor agent progress. - We can identify subtle issues such as privacy leakage, authority escalation, and indirect prompt injection.

Responsibilities:
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- We help train advanced generative systems by providing human feedback on AI agent behavior. - We work on projects that teach models how to plan, coordinate, and optimize complex real-world architectural workflows. - We support the development of proactive, multi-step agents that can operate across broader task sequences. - We evaluate system performance in live scenarios and provide clear, detailed technical observations. - We contribute our software and orchestration expertise to improve how autonomous agents function in practical environments. - We help identify failure modes and edge cases that affect safety, reliability, and execution quality.
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Company:
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We collaborate with leading AI organizations to improve the worlds most advanced autonomous and generative systems through human feedback. Our work centers on training large language models to act as proactive, multi-step agents capable of designing, coordinating, and optimizing complex workflows. This is a role for experienced backend, automation, and systems professionals who want to shape the future of AI agents and contribute to meaningful real-world projects.
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