Software Engineer Task Author (AI Training)

- 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 fintech, enterprise SaaS, or regulated industry software engineering contexts - Background with monitoring and observability platforms such as Datadog, PagerDuty, or Grafana - Experience with microservices architectures or event-driven systems

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