About this role · Coding
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. This role is open to working software engineers across Canada, from Vancouver and Toronto to Montreal and beyond. If you have hands-on experience with production systems, infrastructure code, and real debugging workflows, this is a flexible and rewarding way to contribute to AI development at the frontier. - 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 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 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 enterprise SaaS, e-commerce, telecommunications, or industrial engineering contexts - Background with monitoring and observability platforms such as Datadog, PagerDuty, or Grafana - Familiarity with cloud-native architectures on AWS, GCP, or Azure Why Join Us - Work on cutting-edge AI projects alongside leading research labs - Fully remote and flexible — work when and where it suits you - Freelance autonomy with the structure of meaningful, well-defined task-based work - Contribute directly to how AI systems understand and perform real software engineering - Potential for ongoing work and contract extension as new projects launch