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 🤖

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!

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