This is a solutions engineer role, you own the technical health of your deployments end to end: when the AI gets something wrong, you find out why — digging through conversation logs, refining prompts, analyzing data, and working with engineering on fixes — then you get on a call and explain it to the customer in plain language. You sit at the intersection of product, engineering, and customer success: technical enough to troubleshoot the AI yourself, communicative enough to be your customers' most trusted point of contact.

About Us:**

STAN is the largest provider of AI solutions for HOA and Condo Property Managers. We are using cutting-edge and patented artificial intelligence technology to build solutions that enhance life for residents of more than 2.5 million+ homes across North America. And, we are on a mission to build the world’s first AI property manager. Want to come along for the ride? STAN is also an award-winning platform, having been recognized by Rogers, FedEx, George Brown College, StartUp Canada, the Waterloo Accelerator Centre, and more!

To learn more, feel free to visit us at www.stan(.)ai 🤖

Tasks Serve as the primary technical contact for a small portfolio of enterprise accounts — joining regular customer calls, owning follow-through, and building trusted relationships with stakeholders Troubleshoot conversational AI behavior through prompt engineering: diagnose why the assistant responded a certain way, then iterate on system prompts, escalation flows, and knowledge sources to fix it Review voice and chat conversation logs to identify failure patterns, quality gaps, and improvement opportunities Configure, monitor, and troubleshoot Manager AI back-office automations — diagnosing where workflows break down and getting them back on track Support integrations between STAN and each customer's property management system (PMS) and enterprise applications — APIs, data flows, and debugging across the stack Run data analysis on conversation and automation outcomes — resolution rates, escalation rates, ticket quality — and turn findings into clear, decision-ready reporting for customers and internal teams Explain complex technical situations to non-technical stakeholders: root causes, tradeoffs, and timelines, delivered clearly and credibly Translate customer feedback and recurring issues into structured product input for engineering Requirements 3+ years in SaaS (preferred), ideally in professional services, technical account management, solutions engineering, or a forward-deployed engineering role Real technical depth with AI/LLM-based products: you understand how prompts, context, and model behavior interact, and you troubleshoot systematically rather than by guesswork Basic backend engineering skills — comfortable with APIs, webhooks, reading logs, querying data (SQL), and light scripting (Python or similar) Strong analytical instincts: you can take raw conversation or ticket data and produce a defensible read on what's actually happening Excellent client-facing communication — calm under pressure, credible with executives, precise without jargon Ownership mentality: you close loops, flag risks early, and are comfortable being the accountable name on an enterprise relationship Nice to Have Experience with conversational AI, voice AI, or contact center technology Workflow automation or systems integration experience Exposure to property management software (Yardi, AppFolio, Vantaca, CINC) or the HOA/community management industry Prompt engineering experience in a production environment Benefits Competitive salary Comprehensive health, dental, and specialist benefits. Company Macbook. Free parking and shuttle service to the office. Extra PTO during occasional US holidays. Company events, in-office restaurant, and building-wide perks. Unlimited ping pong and espresso! If you're a closer who is passionate about AI and ready to disrupt a massive industry, we want to talk to you!