Software Engineer Task Author (AI Training)
Alignerr
Bengaluru, Karnataka, IndiaFresher3h agovia LinkedIn
This job at a glance
- Who can apply
- Freshers
- Must know
- REST APIsGitCI/CD
- Nice to have
- AWSAzureGCP
- Work
- On-site in Bengaluru
- Pay
- Not stated by the employer.
- Skill demand
- REST APIs45%Git42%CI/CD17%AWS14%of 99 similar fresher jobs posted in India this week
- Listed
- 27 Oct 2026 · still open
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About the Role
Alignerr is building a dataset of expert tasks to train and evaluate advanced AI agents on real enterprise engineering work. As a Task Author, you will design and calibrate authentic engineering challenges. This role requires hands-on engineering skill and is designed for working engineers with real industry experience in backend systems, SaaS infrastructure, APIs, or enterprise software.
- 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 & Tech Stack
- Working software engineer with hands-on, industry-level experience.
- 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.
- Strong written communication skills in English.
Nice to Have
- Experience in enterprise SaaS, fintech, or industrial IoT engineering contexts.
- Background with monitoring and observability platforms such as Datadog, Grafana, or PagerDuty.
- Familiarity with cloud infrastructure on AWS, GCP, or Azure.