AI Workflow Automation Engineer
Role summary
We are seeking an AI Workflow Automation Engineer to design, build, and refine AI-assisted workflows and agents. This role involves creating high-quality prompt instructions, orchestrating data and tasks across various tools (like Airtable and LLMs), and identifying opportunities to automate manual processes for measurable time savings and improved consistency. You will work with enterprise GenAI tools such as ChatGPT, Claude Enterprise, and Copilot, and partner with product, data, and operational stakeholders to drive adoption and ensure effective usage. The ideal candidate is a hands-on "doer" comfortable operating in ambiguous environments, capable of independently creating and shipping working automations, and ensuring outputs are executive-consumable.
- 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.
