AI Workflow Automation Engineer
Job Description
- Create, test, and refine prompt instructions (persona‑driven where needed) to consistently generate target outputs (newsletters, summaries, status updates, visuals).
- Design and implement AI‑assisted workflows that orchestrate data/tasks across tools (e.g., Airtable workflows into Claude/LLMs; workflow scheduling and output delivery).
- Define desired deliverables first, then reverse‑engineer automation to reliably produce them (output‑first approach).
- Build an organizationally usable agent and drive adoption—partnering with product, data, and operational stakeholders to ensure it is effective and used correctly.
- Identify manual, repetitive cross‑app processes and redesign them into automated workflows with measurable time savings and improved consistency.
- Support standardized reporting outputs (e.g., weekly test status/trend reporting) and implement a human‑in‑the‑loop model when needed.
- Enable internal teams: document how workflows work, provide hands‑on coaching, and help others learn how to maintain or extend automations.
- Work within the existing integrated AI ecosystem (ChatGPT, Claude Enterprise, Copilot; plus CoWork, Gamma, Figma where applicable).
- Demonstrated experience creating high‑quality prompt instructions and iterating them to achieve consistent, reliable outputs.
- Proven ability to design and build AI‑assisted workflows (automation + orchestration), including experimentation and iterative improvement.
- Hands‑on capability to build (not just advise): a “doer” who can independently create and ship working workflows/agents. Comfort operating in ambiguous problems with trial‑and‑error to reach an effective automation outcome.
- Experience working with enterprise GenAI tools such as ChatGPT, Claude Enterprise, and/or Copilot, and integrating them into business workflows.
- Experience structuring operational content in tools like Airtable and orchestrating automations from structured data sources into AI outputs (newsletter generation example).
- Ability to build workflow outputs that are executive‑consumable (clear narratives, appropriate visuals), aligning to the “BI‑minded” requirement for what good output looks like.
- Ability to partner with product, data, and organizational teams to drive adoption and effective usage of the agent/workflows.
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