Sales / Revenue Operations Task Author

About the Role

Alignerr is building a dataset of expert tasks that train and evaluate advanced AI agents on real enterprise work. As a Task Author for the Sales / Revenue Operations role, you will design and calibrate realistic problems that challenge AI agents performing the kinds of work a revenue operations professional faces daily — reconciling account data across CRM, orders, email, and chat to arrive at one defensible answer.

Key Responsibilities

• Author realistic task prompts grounded in revenue operations scenarios (bookings reconciliation, account discrepancies, fulfillment status, recognized revenue).
• Write scoring rubrics that define exactly what a correct answer looks like and how it is evaluated.
• Set up task environments so an AI agent enters a realistic work situation with the same business systems a human employee would use.
• Solve each task yourself to validate soundness and confirm the rubric is accurate.
• Calibrate task difficulty — test tasks against AI models and adjust complexity, ambiguity, or steps until the task reliably challenges the model to the intended degree while remaining objectively gradable.
• Review and correct AI-drafted task prompts or rubrics when provided.

Qualifications

• Hands-on experience in revenue operations, sales operations, or a closely related function at an industrial or enterprise company.
• Deep familiarity with CRM systems (e.g., Salesforce) and the ability to query and interpret account and bookings data.
• Strong understanding of bookings, fulfillment pipelines, and revenue recognition concepts.
• Ability to define precise, verifiable correctness criteria — not just "good judgment" but a standard that can be checked.
• Iterative mindset: willing to test, refine, and re-test until a task is correctly calibrated.
• Comfort operating business communication tools (email, chat) and dashboards as part of multi-system workflows.

Nice to Have

• Experience training or evaluating AI tools in a sales or revenue context.
• Background in enterprise B2B environments with complex deal structures.

What We Screen For

The strongest candidates have done this job in industry, are comfortable with the everyday software of their domain, and can describe — concretely — how they would build a task that reliably challenges a capable AI agent while remaining clearly and objectively gradable.