About The Role

Alignerr is building a dataset of expert tasks that train and evaluate advanced AI agents on real enterprise engineering work. As a Task Author, you will design and calibrate authentic engineering challenges — diagnosing failing integrations from logs, tracing bugs through codebases, and writing and verifying real fixes — that genuinely push the limits of capable AI agents.

London's engineering scene spans fintech, enterprise SaaS, and deep-tech — and this role is built for engineers who operate in that world. If you debug real systems, write infrastructure code, and understand what a production failure actually looks like, your expertise is exactly what we need.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: Flexible, task-based

Key Responsibilities

• Author realistic engineering task prompts covering integration failures, log-based debugging, bug traces through source code, and configuration or integration fixes
• Write scoring rubrics that define exactly what a correct fix or diagnosis looks like and how it is verified — including live environment validation where applicable
• Set up task environments with realistic codebases, logs, alerts, and system states that place an AI agent in a plausible engineering situation
• Solve each task yourself — write the actual fix and confirm it works — to validate the task is sound and the rubric is accurate
• Calibrate task difficulty by adjusting code complexity, log volume, failure modes, or ambiguity until the task reliably challenges the model to the intended degree
• Review and correct AI-drafted task prompts or rubrics when provided