Alignerr is building a dataset of expert tasks that train and evaluate advanced AI agents on real enterprise engineering work. As a Task Author based in Bangalore, 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.
Bangalore's engineering talent is world-class, and this role is designed for working engineers with real industry experience in backend systems, SaaS infrastructure, APIs, or enterprise software. This is not a generalist or instructional role — it requires hands-on engineering skill.
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 setting 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
Qualifications
Working software engineer with hands-on, industry-level experience — 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 infrastructur