AI Training Task Architect — Remote Contract

Dorado; Greater London; On-site; GBP 55,104 - 96,432; Part time

Job summary

Alignerr is building a dataset of expert tasks to train and evaluate advanced AI agents. As a Task Author, you will design authentic engineering challenges, diagnose failing integrations from logs, trace bugs, and write real fixes that push AI agents beyond current capabilities.

London's engineering scene spans fintech, enterprise SaaS, and deep-tech, and this role targets engineers who operate in that world.

Qualifications

• Working software engineer with hands-on, industry-level experience.
• Fluency in Git, version control workflows, and code review practices.
• Strong debugging skills: reading logs, tracing failures through codebase.
• Experience with infrastructure, integrations, and configuration code (APIs, services, CI/CD).
• Ability to write and verify a code fix in live or simulated environments.

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.

Skills

Git workflows

Debugging

Observability tools

CI/CD

Code review

Tools

Datadog

PagerDuty

Grafana

Job description

Alignerr is building a dataset of expert tasks to train and evaluate advanced AI agents. As a Task Author, you will design authentic engineering challenges, diagnose failing integrations from logs, trace bugs, and write real fixes that push AI agents beyond current capabilities.

London's engineering scene spans fintech, enterprise SaaS, and deep-tech, and this role targets engineers who operate in that world.