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Software Engineer Task Author (AI Training)

Alignerr / Software Engineer Task Author (AI Training)

RATE

$70-$120/HR

LOCATION

REMOTE (GLOBAL)

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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. London's engineering scene spans fintech, enterprise SaaS, and deep-tech — and this role is built for engineers who operate in that world. If you debug real systems, write infrastructure code, and understand what a production failure actually looks like, your expertise is exactly what we need. - **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 ###

REQUIREMENTS

▸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