The RoleWe're hiring an
Engineering Manager to lead our Maintenance team - the product area at the heart of what our customers use every day. You'll own the roadmap, the team's health, and delivery. You'll be in the code when it matters, in front of customers when it matters, and leading your team through a period where AI is fundamentally reshaping how software gets built.
We're looking for a
technically strong, product-minded, and versatile leader who can move fast, adapt faster, and lead engineers into the age of AI-native development.
What You'll Do- Lead the Maintenance team. Set direction, grow people, and run a healthy delivery cadence from intake through shipping and production.
- Grow your engineers. Run real 1:1s, give honest feedback, and take career development seriously. The best EMs make the people around them better.
- Translate customer needs into technical direction. Work shoulder-to-shoulder with Product, CS, and Implementation. Sit in on customer calls when depth is needed, and turn what enterprise operators are asking for into something your team can build.
- Stay hands-on. You'll still write code, maybe not every day, but meaningfully. Prototyping, unblocking your team, jumping into incidents, reviewing PRs that matter. You set the technical bar by occasionally clearing it yourself.
- Champion AI-native ways of working. Our engineers increasingly pair with Claude, Copilot, and agentic tooling. You'll help the team figure out what works and ship more value with fewer hands on the keyboard.
- Own production. On-call culture, incident response, observability (Datadog), and the long tail of reliability work.
What We're Looking ForBaseline: you can read code - and write it when it matters. You're credible in the code, able to open a PR, push back when something looks off, and contribute directly when the situation calls for it.
- 5+ years of engineering experience, with 2-3+ years managing engineers.
- 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.
- 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?"
- A fast learner who experiments relentlessly. We're actively building AI agents into our product and need a leader who can pick this up fast - running experiments, learning from what breaks, and shipping. Prior experience deploying AI agents at scale is a strong plus.
- Comfortable in front of enterprise customers, equally at home with a CTO or a frontline operator.
- Experience owning production services: on-call, incident response, and the observability stack that makes it tractable.
Nice to Have- Background in PropTech, multifamily, or enterprise SaaS.
- Familiarity with our stack: Node.js, Angular, MongoDB, and AWS.
- Experience with message queues, pub/sub, or caching layers - Redis, Kafka, RabbitMQ, or similar.
What's In It For You- Real ownership. You're not a cog in a 200-person engineering org. You'll own a core product area end-to-end, from roadmap to production, and your decisions will land in front of the largest multifamily operators in North America.
- Close to the customer. SuiteSpot engineers aren't abstracted away from the business. You'll talk to the people using what you build, see the impact, and carry real signal back into the team.
- AI-forward by default. We're not debating whether AI changes how we build - we're figuring out how to do it best, and we want a leader who wants to figure it out with us.
- A team that ships. Engineers, CSMs, and Implementation leads who take customer outcomes personally and move fast together.
Hiring ProcessWe aim to move quickly and respect your time. The process has five stages:
- Initial screen (30 min) - introduction, role overview, mutual fit.
- Technical screener - a short async coding exercise via CoderByte to confirm the technical baseline.
- Hiring manager interview (45-60 min) - deeper conversation on your experience, leadership style, and how you think about the role.
- Onsite - two technical rounds: a coding round where we encourage use of AI tools (we'll share details ahead of time so you can prepare in the environment you work in), and a system design discussion focused on how you reason through trade-offs.
- Executive conversation - meet our engineering leadership to align on direction and close out any remaining questions.
We provide feedback at every stage and aim to move from first conversation to offer within 3-4 weeks.
#LI-Hybrid
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