Job Description:
Job Description: Product Operations Builder Role Overview We are looking for a Product Operations Builder who thrives at the intersection of operations, technology, and execution. This role is for someone who doesn’t just identify problems—but personally builds working solutions. You will embed directly with operational teams, uncover inefficiencies, and ship practical automations, internal tools, and AI-powered workflows that make teams faster and more effective. This is not a traditional product management role, nor is it a pure engineering position. Success here requires strong product instincts, hands-on building ability, and a deep understanding of how operational work actually happens day to day. What You’ll Be Responsible For Operational Problem Solving Work directly alongside Operations, Fulfillment, and Customer Experience teams to observe workflows and uncover bottlenecks. Translate recurring friction, escalations, and manual work into clearly defined, solvable problems. Prioritize issues based on measurable business impact rather than theoretical value. Hands-On Solution Building Design and deploy working automations and internal tools using a mix of no-code/low-code platforms (e.g., automation builders and workflow tools), AI/LLM APIs, and lightweight custom scripting. Build solutions end-to-end—from idea through deployment and iteration—without waiting on large engineering cycles. Continuously refine automations based on real usage and feedback. Outcome Ownership Define success metrics for every solution (e.g., reduced handle time, fewer escalations, lower manual effort, cost savings). Track and report “before and after” results—you own outcomes, not just delivery. Retire or refactor tools that do not deliver meaningful impact. Tooling Strategy & Integration Maintain a prioritized backlog of tooling and automation opportunities across the business. Partner with Product and Engineering teams to determine which initiatives remain lightweight builds versus those that warrant deeper platform investment. Own simple integrations between core business systems (support platforms, documentation tools, internal systems) to reduce context switching and improve information flow. AI Enablement Identify opportunities where AI meaningfully improves productivity and decision-making—not novelty use cases. Evaluate AI vendors and tools, run small pilots, and support adoption across teams. Apply LLMs pragmatically using techniques such as prompt engineering, RAG workflows, agent patterns, and API integrations.
