Software Engineer Task Author (AI Training)

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 is hands-on engineering work. Generalist or theoretical profiles cannot do this. If you're a working software engineer who debugs real systems for a living, this is a rare opportunity to shape how the next generation of AI understands engineering. Organization: AlignerrType: Hourly ContractLocation: RemoteCommitment: 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 fixesWrite scoring rubrics that define exactly what a correct fix or diagnosis looks like and how it is verified — including live environment validation where applicableSet up task environments with realistic codebases, logs, alerts, and system states that place an AI agent in a plausible engineering situationSolve each task yourself — write the actual fix and confirm it works — to validate the task is sound and the rubric is accurateCalibrate task difficulty by adjusting code complexity, log volume, failure modes, or ambiguity until the task reliably challenges the model to the intended degreeReview 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 roleFluency in Git, version control workflows, and code review practicesStrong debugging skills: comfortable reading logs, using observability tools, and tracing failures through a codebaseExperience 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 environmentAbility to define precise, checkable correctness criteria for engineering outcomes Nice to Have Experience in enterprise SaaS, financial technology, or large-scale distributed systemsBackground with monitoring and observability platforms such as Datadog, PagerDuty, or GrafanaFamiliarity with AI tools or developer platforms as an end user Why Join Us Work on cutting-edge AI projects alongside leading research labsFully remote and flexible — work when and where it suits youFreelance autonomy with the structure of meaningful, well-defined task-based workContribute directly to how AI systems understand and perform real software engineeringPotential for ongoing work and contract extension as new projects launch