Forward Deployed Engineer

This is a forward deployed 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 🤖

• 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

• 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

• 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