Senior Software Engineer - SAM AI

SuiteSpot Technology•Toronto, ON

2d•Hybrid

About The Position

SuiteSpot is a PropTech company transforming how residential real estate is managed and operated at scale. Our award-winning Maintenance and Capital SaaS solutions serve the top 50 multifamily property management operators in North America, helping them streamline operations across hundreds of thousands of units. We move fast, ship real solutions, and measure ourselves by customer outcomes. Our engineering team operates with high autonomy and direct customer impact. We live by P.I.E. — Passion, Integrity, and Execution — and look for people who do the same. About the SAM Team SAM is SuiteSpot's specialized AI agent for resident maintenance. It manages every interaction from request to resolution: voice and chat, 35+ languages, 24/7. SAM detects emergencies in real time and escalates them, walks residents through mitigation while help is on the way, and deflects non-maintenance calls so the front office stays focused. The team is small and ships fast. We're expanding SAM beyond resident maintenance into more of the platform, with plenty of greenfield ahead. This is the part of SuiteSpot where the AI is the product. The Role We're hiring a Senior Software Engineer to build and scale SAM. You'll own features across the full stack — Node.js services, Angular frontends, MongoDB, plus the AI agent layer that powers SAM Voice and SAM Chat — and ship them into a 24/7 production service customers depend on for emergencies. This isn't a big company where your code sits in review queues for weeks. What you build today can be in production tomorrow, handling real resident calls and chats across hundreds of thousands of apartments in North America. You'll contribute to architecture decisions and help set the technical direction for the team. You'll report to an Engineering Manager and collaborate with product, design, and other engineers.

Requirements

5+ years of engineering experience.
Versatile across the stack. You are comfortable across backend, frontend, data, and infrastructure. You have a well-developed sense of what good software looks like — clean architecture, sensible trade-offs, maintainable design — and can spot when something isn't. You are familiar with Node.js, Angular, MongoDB, and AWS.
1+ years of hands-on experience building platform‑level AI capabilities.
Product-minded. You ask "what does this do for the customer?" and "is this the highest-value thing we could be doing?" before "how should we build it?"
Ownership mentality. You don't wait to be told what to do. You see a problem, figure out what needs to be built, and drive it to completion. You're accountable for outcomes, not just output.
Fast learner. AI tools, models, and patterns change fast. You pick up new ones quickly and bring the rest of the team along.
Comfortable owning production. You're at home with on-call rotation, incident response, and observability tooling (Datadog).
Experience with message queues, pub/sub, or caching layers — Redis, Kafka, RabbitMQ, or similar.

Nice To Haves

Experience with Agentic Engineering tools like Claude Code, OpenCode, Pi Coding Agent, Cline, Kilo, etc.
Experience with AI Engineering: Prompt Engineering, RAG, CAG, or similar.
Experience with telephony, voice, or IVR systems.
Background in PropTech, multifamily, or enterprise SaaS.

Responsibilities

Own problems end-to-end from technical design through deployment and iteration
Tune and improve agent behavior through prompt iteration, evals, and instrumentation that tells you when SAM is getting it right or wrong
Drive conversation quality across voice and chat — accuracy, latency, escalation logic, and the edge cases real residents bring
Own production reliability for a 24/7 mission-critical service, including on-call rotation, incident response, and Datadog observability
Investigate and resolve customer-reported issues by pulling call recordings, transcripts, and traces, fixing the underlying behavior, and feeding the learnings back into the system
Shape technical direction through architecture decisions, code reviews, and engineering best practices