Workflow Annotator — Software Engineering
Job Description
Role Title: Workflow Annotator — Software Engineering
Role Type: Contractor
Location: Remote
micro1 is engaging Workflow Annotator — Software Engineering experts to contribute to a dynamic customer project focused on building a library of realistic, multi-step engineering workflows. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
Design and author detailed, multi-step task scenarios reflecting authentic software engineering activities, such as pull request management, issue triage, merge conflict resolution, and CI configuration updates using GitHub.
Execute and document each workflow in real time within actual tools, capturing every step, rationale, edge case, and decision point to ensure comprehensive and accurate records.
Integrate supplemental collaboration tools where appropriate (Slack, Microsoft 365/Google Workspace, Snowflake) to create end-to-end scenarios mirroring real engineering processes.
Produce clear, structured documentation for each workflow, including step sequencing, intent at each stage, expected outcomes, and visual artifacts (screenshots, logs) as needed for effective annotation.
Flag ambiguous or unrealistic scenarios to the data program team and refine workflows based on feedback to maximize realism and utility for annotation purposes.
Work within the Agora internal annotation platform to submit deliverables and collaborate with project leads.
Preferred Qualifications
Minimum 2 years of professional experience in software engineering with daily use of GitHub-centered workflows.
Strong command of written English, with an emphasis on clarity, consistency, and attention to detail in documenting processes for others to follow.
Hands-on familiarity with Slack and Microsoft 365 or Google Workspace as part of regular engineering activities.
Experience designing or participating in code review, versioning, branching, or release workflows.
Exposure to CI/CD pipelines, code review platforms, or systems for process documentation is an advantage.
Basic skills in SQL (preferably with Snowflake) are a plus, though not required.
Prior experience with data annotation, technical writing, or QA documentation is a bonus.
About Micro1
Micro1 is building the essential infrastructure for the next generation of artificial intelligence, moving beyond the limitations of static datasets to create a dynamic ecosystem where models truly learn to think and act. At its core, the company understands that the path to frontier intelligence isn't paved with synthetic data alone; it requires the nuance, judgment, and contextual awareness that only expert human guidance can provide. By positioning itself at the intersection of human expertise and advanced reinforcement learning, Micro1 is tackling the hardest problem in AI today: teaching models not just to answer questions, but to reason through complexity and take meaningful actions in unpredictable, real-world environments.
This mission comes to life through Realm, Micro1's flagship training environment. Realm functions as a high-fidelity simulation ground where AI agents are immersed in scenarios that closely mirror the messiness of actual human workflows. Rather than relying on abstract benchmarks, Realm forces models to engage in agentic actions, multi-step decisions, digital navigation, coding, and problem-solving that require genuine comprehension. It is within these realistic sandboxes that world-class human data is generated, creating a continuous feedback loop where expert annotators observe, correct, and guide model behavior. This process does more than just fine-tune outputs; it fundamentally elevates a model's underlying reasoning architecture, ensuring that the intelligence developed in training holds up when deployed into the wild.
But training is only half the equation. Micro1 recognizes that the true test of an AI system lies in its production performance, which is where Cortex enters the picture. Cortex is a contextual evaluation platform designed to move beyond superficial accuracy metrics and provide a granular, real-time view of how agents behave in live settings. It doesn't just flag errors; it surfaces the underlying context behind failures, revealing why an agent struggled with a particular user intent or environmental variable. This insight is invaluable for engineering teams, as it transforms evaluation from a passive checkpoint into an active improvement tool. With Cortex, companies can catch degradation early, understand the nuances of edge cases, and feed those learnings directly back into Realm for retraining, creating a virtuous cycle of continuous advancement.
Ultimately, Micro1 is not merely a data lab or an evaluation tool it is a comprehensive intelligence engine that connects the entire lifecycle of model development. From the expert human feedback that sharpens raw capability, to the realistic RL environments that forge robust agentic behavior, to the contextual oversight that ensures reliability in production, Micro1 provides the integrated foundation that AI labs and enterprises desperately need. As the industry races toward truly autonomous systems, Micro1 stands as the critical bridge between laboratory breakthroughs and dependable, real-world impact, ensuring that frontier models do not just perform well on paper, but deliver genuine value in the complex, dynamic world they are meant to serve.