Staff Engineer (Backend, DevOps, Infrastructure)

Zuma is pioneering the future of agentic AI and our focus is to transform the rental market experience for consumers and property manager alike. Our innovative platform is engineered from the ground up to boost operations efficiency and enhance support capabilities for property management business across the US and Canada, a ~$200B market.

Off the back of our Series-A in early 2024, Zuma is scaling rapidly. Achieving our vision requires a team of passionate, innovative individuals eager to leverage technology to redefine customer-business interactions. We're on the hunt for exceptional talent ready to join our mission and contribute to building a groundbreaking technology that reshapes how businesses engage with customers.

Zuma has raised over $17M in funding to date and has support from world-renowned investors, including Andreessen Horowitz (a16z), Y Combinator, King River, Range Ventures, and distinguished angel investors like YC’s former COO, Qasar Younis.

Help define how humans collaborate with intelligent systems in one of the largest and most underserved industries in the world: property management.

You’ll shape the technical foundation of a platform that is not just supporting human workflows, but executing them autonomously through AI agents. This is a rare opportunity to influence how an entire industry evolves, building tools that transform repetitive operational tasks into seamless, intelligent experiences.

Your work will directly contribute to how trust is built between humans and machines, how operations scale without added headcount, and how residents and staff experience a new, AI-powered standard of service.

We’re not just building software we’re designing AI that people want to work with. Delightful, trustworthy, and deeply effective.

Join us to help lead the AI revolution in multifamily, drive meaningful real-world impact, and be part of reimagining what work can feel like when done side-by-side with intelligent agents.

You will be a cornerstone of our engineering organization, reporting to the VPE. This is a pivotal role where you'll lead critical system rewrites, architect scalable foundations for our AI platform, and establish the technical standards that will shape our engineering culture for years to come.

You'll work at the intersection of cutting-edge LLM technology and practical business applications, creating sophisticated systems that power our AI leasing agent while building self-serve experiences that enable rapid customer onboarding. As our first US-based engineer, you'll bridge the gap between our product vision and technical implementation.

This role offers a rare opportunity to directly influence how we architect the next generation of our platform. You'll tackle projects like rebuilding our onboarding/configuration system to be self-serve, creating robust analytics infrastructure to measure AI performance, and reimagining our integration framework to connect seamlessly with customer systems. Your work will significantly reduce manual engineering overhead while enabling rapid scaling of our customer base.

We're looking for a Staff Engineer to help us bring that future to life.

This is not just another dev role. You'll be hands-on shaping the technical DNA of Zuma. You'll architect critical systems, tame legacy code, build net-new AI-powered experiences, and lay down the patterns future engineers will inherit. If you're obsessed with building real products people use, especially products powered by LLMs, this might be your playground.

Every commit should trace back to resident or operator value. Whether it’s a new feature, infra investment, or AI capability, if it doesn’t solve a real problem, it doesn’t ship.

We favor composable primitives over clever abstractions. Open standards, clean APIs, and clear contracts win over custom complexity, even if the custom version is cooler.

Quality is built-in from day one. Our definition of done includes: test coverage, performance checks, basic observability, and internal docs. Shipping fast doesn’t mean skipping craftsmanship.

We use data to guide, not paralyze, our decision-making. We track leading indicators (cycle time, defect rate, NPS) and lagging signals (retention, revenue impact). We keep instrumentation lightweight but meaningful signal over spreadsheet.

Good ideas don’t expire in Zoom. We operate in public inside the company, TDDs, PR reviews, and Linear tickets tell the story. This keeps us async-friendly, auditable, and aligned across time zones and functions.