Software Engineer Task Author
About this role
Alignerr is building a dataset of expert tasks that train and evaluate advanced AI agents on real enterprise work. As a Task Author for the Software Engineer role, you will design and calibrate real engineering tasks — diagnosing failing integrations from logs, tracing bugs through a codebase, and writing and verifying fixes — that genuinely challenge a capable AI agent. This role requires hands-on engineering skill; generalist profiles cannot do this work. Key Responsibilities - Author realistic engineering task prompts: 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 drop an AI agent into 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 — adjust 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. Qualifications - Working software engineer with hands-on experience in industry — this is not a theoretical or instructional role. - Fluency in Git, version control workflows, and code review practices. - Strong debugging skills: comfortable reading logs, using observability tools, and tracing failures through a codebase. - Experience with infrastructure, integrations, and configuration code (APIs, services, config files, CI/CD). - Ability to write and verify a code fix in a live or simulated environment. - Ability to define precise, checkable correctness criteria for engineering outcomes. Nice to Have - Experience in manufacturing, industrial IoT, or enterprise SaaS engineering contexts. - Background with monitoring/observability platforms (e.g., Datadog, PagerDuty, Grafana).
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