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Alpineo Consulting is seeking an Automation Tester to maintain and evolve automation workflows built on Power Automate, including Desktop flows, while moving toward API-driven integrations and code-backed interactions.
You will grow your C# / .NET skills and work with AI coding tools like Claude to design scalable, reliable solutions. Strong judgment and reliability are essential as the team shifts from clicks to robust, API-centric automation.
We are looking for an Automation Engineer to keep our automation running today — and help us build what replaces it tomorrow.
The honest version: RPA got us here, but it's not where we're going. Platforms like Partner Center are opening up real APIs, and we're moving to them wherever we can.
This role lives on both sides of that shift — keeping our existing Power Automate flows healthy and reliable while we rebuild those interactions as API-driven, code-backed integrations.
You know Power Automate cold, you're starting to write real code, and you'd rather direct AI to build the right thing than hand‑write the wrong one.
You own our existing Power Automate estate — cloud flows and Desktop (PAD).
Keep them running, fix them when Microsoft changes something underneath us, and know them well enough to say what's worth maintaining and what should be rebuilt.
As platforms expose APIs, you help move interactions off the RPA frontend and onto real integrations — increasingly in C#.
You don't need to be a strong developer on day one. You need to be clearly on that path and want it. Orchestrating AI, Not Just Prompting It: A lot of the code here gets written with Claude. Your job isn't to type it — it's to know what "good" looks like, break the problem down, hand the right pieces to AI, weigh the options it gives back, and choose the one that actually scales. Working AI-Native, Not AI-Curious: Your daily workflow is deeply integrated with AI. This isn't a perk we offer. It's how we operate.
We don't want someone who accepts whatever AI hands them. We want someone who owns the thinking around it: What we're actually trying to accomplish, and why. What the real goal is — not just the ticket. How it could be done, and what the options on the table are. What to delegate to AI, and how to frame it. How to explore those options with AI instead of settling for its first answer. How to pick the best one: the maintainable one, the one that scales. If that's how you already think, you'll do well here.