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Software Engineer Task Author (AI Training)

Alignerr

Engineering & Development Contractor
Remote (Global) $70 – $120/hr June 26, 2026

Job description

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: 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, financial technology, or large-scale distributed systems
  • Background with monitoring and observability platforms such as Datadog, PagerDuty, or Grafana
  • Familiarity with AI tools or developer platforms as an end user

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
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