Sales & Revenue Operations Task Author (AI Training)

Alignerr Corp.; United States; Remote; USD 33,000 - 67,000; Part time

Job summary

Alignerr Corp. is hiring a Task Author for the Sales / Revenue Operations role to design and calibrate realistic prompts and scoring rubrics for AI agents.

This fully remote, hourly contract targets experienced RevOps professionals with Salesforce familiarity, data interpretation skills, and a disciplined, test-and-iterate mindset to ensure tasks are objective and gradable.

Qualifications

• Hands-on RevOps or SalesOps experience at an industrial or enterprise company.
• Deep familiarity with CRM systems (Salesforce) and the ability to query and interpret data.
• Strong understanding of bookings, fulfillment pipelines, and revenue recognition.
• Ability to define precise, verifiable correctness criteria and iterate calibration.

Responsibilities

• Design and calibrate realistic revenue operations tasks for AI evaluation.
• Write scoring rubrics that clearly define correct answers.
• Set up task environments that mimic enterprise systems.
• Validate task soundness by solving tasks yourself.
• Calibrate task difficulty to challenge AI models while remaining gradable.
• Review and correct AI-drafted prompts and rubrics.

Skills

RevOps experience

SalesOps

Salesforce CRM

Revenue recognition

Data interpretation

English writing

Tools

Email

Chat

Dashboards

Job description

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.

This is a fully remote, flexible contract role well suited to experienced RevOps and SalesOps professionals across Germany --- particularly those with deep exposure to enterprise B2B environments --- who want to contribute meaningfully to the development of advanced AI systems.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: Flexible

Key Responsibilities

• Author realistic task prompts grounded in revenue operations scenarios --- bookings reconciliation, account discrepancies, fulfillment status, and 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
• Strong written English communication skills (all task authoring is conducted in English)

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.