We are seeking experienced Engineering Leaders or Product Leaders to provide expert insight as part of a project for our AI Marketplace. No preparation required — just your real-world experience This is a one-time, paid, project-based interview engaged on a contract basis— not a full-time role. Location: U.S.-based experts only Engagement: One-time, project-based interview
Work Type: Remote Estimated rate: $155/hour (prorated for the 30-minute task)
What You’ll Do:
You’ll complete a ~30-minute recorded AI-led video interview where you explain how you actually do your work in practice. This interview will focus on: Scaling systems across users or teams Managing complexity and governance at scale Deciding what to scale and when Deprecation and migration workflows You will be asked to explain workflows specifically within: scaling systems and lifecycle transitions. You should only apply if you can confidently walk through these areas step-by-step based on your own experience and respond to AI-led interview questions with depth, clarity, and real-world examples.
What We’re Looking For:
10 years in senior engineering leadership, platform engineering, or product leadership focused on system scaling and lifecycle management. Direct, hands-on experience in scaling systems and lifecycle transitions. Experience making or influencing decisions related to scaling strategy, system evolution, and deprecation. Familiarity with tools such as: Jira, Confluence, architecture tools, platform systems. Strong ability to clearly explain workflows, decisions, and reasoning Experience owning or directly executing these workflows in a real production environment About the Interview The interview is designed to elicit step-by-step explanations of real workflows and decision-making processes, with an emphasis on detailed, experience-based responses rather than high-level summaries. This is a project-based engagement. Selected participants will be paid for completing a recorded AI-led video interview; hourly rates are estimates based upon anticipated time of completion. Participants will control their own schedule, provide their own tools to complete the interview, and may participate in other opportunities as they choose. Once you complete the interview, we’ll send your video recording and transcript, along with AI-generated insights, to the internal research team and AI lab partner. This data will be used to generate a structured list of tasks associated with your profession and for AI model improvement. Linked In Global Data Privacy Notice for Job Candidates: https://legal.linkedin.com/content/dam/legal/Global-Data-Privacy-Notice_LI_TalentCommunity.pdf
