We are seeking experienced data platform engineers and data reliability engineers (or infrastructure-oriented data engineers) 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: $130/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:

• Managing DAG dependencies, orchestration, scheduling, and environment parity
• Monitoring freshness, volume, quality drift, cost spikes, and SLA misses
• Triage and classification of data incidents from detection to consumer notification
• Routing observability findings into backlog improvements and platform fixes

You will be asked to explain workflows specifically within: orchestration, monitoring, incident triage, SLA management, observability, and reliability improvement workflows.

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

• 6+ years in data platform engineering, data reliability engineering, or pipeline operations
• Direct, hands-on experience in orchestration, monitoring, incident triage, SLA management, observability, and reliability improvement workflows
• Experience making or influencing decisions related to alert thresholds, blocking versus warning failures, incident classification, SLA escalation, operational ownership, and recovery path
• Familiarity with tools such as: Airflow, Dagster, Prefect, dbt Cloud, Datadog, Monte Carlo, Bigeye, Prometheus, Grafana, Datafold, PagerDuty
• Strong ability to clearly explain workflows, decisions, and reasoning
• Experience owning or directly executing these workflows in a real production environment
• Experience working cross-functionally with HR, legal, payroll, finance, HRIS, business leaders, people managers, or compensation committee stakeholders as relevant to the workflow

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.

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