Product Specialist

Product Specialist

This role sits at the intersection of product quality, technical data accuracy, and operational execution within a fast-growing technology environment focused on heavy equipment intelligence. You will be responsible for ensuring that structured equipment data powering the platform is accurate, complete, and useful for end users such as technicians, operators, and dealers. Acting as both a domain expert and a data steward, you will validate, enrich, and correct technical content drawn from manuals, specifications, and other OEM sources. The role combines hands-on data work with critical review of system outputs, including AI-generated responses, to ensure real-world accuracy. You will also collaborate with internal teams and external partners to improve workflows, maintain quality standards, and scale data operations. This is a highly detail-oriented role where technical understanding and precision directly shape product reliability and user trust.

Accountabilities:

In this role, you will ensure the accuracy, consistency, and usability of equipment data while supporting product quality, operational workflows, and cross-functional coordination.

• Review, structure, and enter technical equipment data from manuals, specifications, and other source documentation into internal systems.
• Apply hands-on equipment knowledge to validate the accuracy and real-world relevance of data entries and product content.
• Tag, categorize, and enrich data using metadata, keywords, and structured frameworks to improve searchability and usability.
• Verify AI-generated or system-produced outputs against source materials, identifying inaccuracies, gaps, or incomplete technical context.
• Add corrections, annotations, and contextual insights to improve clarity, correctness, and usefulness of product responses.
• Cross-reference product outputs with OEM documentation, service manuals, and technical bulletins to ensure factual reliability.
• Identify recurring data issues, quality gaps, or inconsistencies and escalate findings to improve product integrity.
• Support coordination with external partners by communicating requirements, reviewing deliverables, and ensuring alignment with quality standards.
• Manage work queues, track progress, and help ensure deadlines and operational targets are met across data workflows.
• Contribute to defining and improving internal processes, QA guidelines, and structured evaluation frameworks for data quality.

Requirements:

• Experience in data entry, product operations, technical content review, or similar detail-oriented roles.
• Strong familiarity with heavy equipment (agriculture, construction, or related industries) through hands-on work or professional experience.
• Ability to read and interpret technical documentation such as service manuals, parts catalogs, and equipment specifications.
• Strong analytical mindset with the ability to assess whether technical outputs are accurate, not just well-written.
• Excellent attention to detail with a commitment to data accuracy and consistency across large volumes of information.
• Strong written communication skills and ability to document corrections, findings, and structured feedback clearly.
• Ability to work independently in a remote-first environment while managing multiple priorities and deadlines.
• Experience with task management tools, spreadsheets, or data workflows is an asset.
• Basic experience in project coordination or working with distributed or third-party teams is an advantage.

Nice to have:

• Direct hands-on experience as a technician, operator, service writer, or parts specialist in heavy equipment environments.
• Exposure to OEM systems, telematics platforms, or dealer service workflows.
• Experience supporting data annotation, AI/ML datasets, or structured QA processes.
• Strong process-oriented mindset with experience improving operational workflows.

Benefits:

• Competitive compensation package including salary, equity (ESOP), and benefits.
• Remote-first work environment with flexibility and autonomy.
• Opportunity to work on innovative data and AI-driven products in the heavy equipment space.
• Collaborative, learning-focused culture that values growth and impact.
• Exposure to complex, real-world technical datasets and meaningful product challenges.
• Opportunity to contribute to improving data quality systems and operational frameworks.
• Work within a team with proven entrepreneurial leadership and strong industry experience.