Review and enter structured data from documents and raw sources into our platform, including equipment service manuals, technical specifications, parts information, and operator guides.
Apply equipment domain knowledge to validate that data entries are technically accurate, contextually correct, and consistent with how equipment is actually used in the field.
Assign metadata, categories, and keywords to improve searchability, consistency, and usability across the product.
Verify that AI-generated or system-produced answers, recommendations, and outputs are accurate, complete, and aligned with the source documentation — flagging anything misleading, incomplete, or technically incorrect.
Add contextual notes, corrections, or clarifications to improve the accuracy and usefulness of product responses.
Identify patterns, errors, or gaps in equipment data and escalate appropriately to ensure nothing falls through the cracks.
Serve as a domain-informed reviewer of product outputs, ensuring that answers, search results, and recommendations reflect real-world equipment knowledge and not just surface-level pattern matching.
Cross-reference product responses against source materials (service manuals, OEM documentation, technical bulletins) to confirm factual accuracy.
Develop and maintain a working understanding of common equipment failure modes, maintenance procedures, and service workflows to better evaluate the quality of product outputs.
Proactively identify cases where the product is producing answers that are technically plausible but incorrect, incomplete, or missing important safety or procedural context.
Contribute to building internal QA checklists, rubrics, and benchmarks for evaluating answer quality over time.
Work closely with external partners to communicate requirements, provide clarifications, and ensure alignment with internal standards.
Help manage work queues, assign tasks (internally or externally), and track progress against deadlines.
Review partner outputs with a critical eye for both process compliance and equipment accuracy, providing structured feedback and collaborating to continuously improve quality.
Help define, document, and refine data entry guidelines, workflows, and standard operating procedures — including equipment-specific guidelines for how technical content should be structured and reviewed.
Identify inefficiencies in data processing workflows and recommend improvements.
Track key metrics (accuracy rates, quality scores, throughput, turnaround time) and provide regular updates to stakeholders.
Requirements
Strong attention to detail and commitment to accuracy, especially when working with technical content.
Hands-on or professional familiarity with heavy equipment — particularly in agriculture or construction — is highly valued.
Ability to read and interpret equipment service manuals, technical specifications, or parts documentation.
Comfortable evaluating whether a technical answer is correct, not just whether it sounds correct.
Ability to follow structured guidelines and apply them consistently across large volumes of content.
Strong written communication skills.
Comfortable working independently in a remote environment.
Experience with data entry, annotation, or content management tools is an asset — training will be provided.
Basic project management or task coordination experience.
Experience working with third-party vendors or distributed teams.
Familiarity with project tracking tools (e.g., spreadsheets, task management platforms).
Ability to manage multiple priorities and deadlines in a fast-paced environment.
Benefits
Join a proven team led by serial entrepreneur Remi Schmaltz that has successfully exited 2 previous agriculture companies.
Remote-first role with a flexible work environment.
Opportunity to contribute to meaningful projects in the growing field of data and information management.
Contribute to an innovative product team shaping the future of AI in the large equipment space.
A collaborative culture that values growth, learning, and impact.