AI Workflow Engineer | LATAM

Responsibilities

• Take scoped use cases from the Director, AI Enablement and build working solutions: prompt layers, automation flows, lightweight agents, RAG implementations, and API integrations that connect AI tools to the systems business teams already use
• Build working prototypes quickly - the goal is to show a team what is possible in days, not weeks, then refine based on what actually lands
• Translate a documented workflow assessment into a technical design, select the right tools for the job, and own the build through to a deployable solution
• Maintain solution documentation that is clear enough for handoff, iteration, and audit - not just for engineers, but for the business owner who will live with it
• Spend time inside the functions you are building for - Finance, HR, Legal, Marketing Ops, Customer Success, and others - understanding how the work actually flows before you redesign it
• Run working sessions with team members to map current-state workflows, surface friction points, and identify where AI creates real leverage versus where it creates noise
• Build credibility with non-technical stakeholders by showing them working solutions, not decks - and by being honest about what will and will not work
• Support user acceptance testing and early adoption, troubleshooting issues close to launch and iterating based on real usage
• Build demos and proof-of-concepts that help the Director, AI Enablement make the case for a use case - or disqualify it early before resources are committed
• Contribute to vendor and tool evaluations with a builder's perspective: not just whether a tool claims to do something, but whether it actually works in the context of a specific workflow
• Feed learnings from the build process back into the program - what worked, what did not, what should be standardized across functions
• Work on tactical quick wins and longer-horizon strategic builds at the same time, switching contexts across active use cases as priorities shift