Staff Engineer (Agentic AI & Data)

About Zuma Zuma is pioneering the future of agentic AI and our focus is to transform the rental market experience for consumers and property managers alike. Our innovative platform is engineered from the ground up to boost operations efficiency and enhance support capabilities for property management businesses across the U.S. 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. Zuma has raised over $17 M 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 such as YC’s former COO, Qasar Younis. Role Overview As a Staff Engineer, you will help define how humans collaborate with intelligent systems in the property management industry. You’ll shape the technical foundation of a platform that not only supports human workflows but executes them autonomously through AI agents. Your work will directly contribute to building trust between humans and machines, scaling operations without added headcount, and elevating the experience for residents and staff. We’re not just building software; we’re designing AI that people want to work with—delightful, trustworthy, and deeply effective. Join us to lead the AI revolution in multifamily, drive meaningful real‑world impact, and help reimagine what work can feel like when done side‑by‑side with intelligent agents. Responsibilities Architect and build critical systems for Zuma’s AI platform, focusing on scalable, agentic architectures. Lead major technical rewrites and establish engineering standards that shape culture for years to come. Build self‑serve onboarding/configuration systems, robust analytics infrastructure, and integration frameworks that seamlessly connect with customer systems. Work directly with cutting‑edge LLM technology, fine‑tune models, and integrate them into production‑grade software used by real users. Collaborate closely with product to translate customer needs into technical solutions. Craft intelligent configuration interfaces that allow the AI to adapt to individual customer requirements. Design and implement integration frameworks that connect AI with customer systems. Establish modern engineering practices, infrastructure, and observability for an AI‑first product. Implement analytics to measure and continuously improve AI effectiveness. Lead development of innovative features that push the boundaries of AI in real‑estate. Mentor engineers and elevate team capabilities around LLM technologies. Interact directly with customers to understand their needs and occasionally travel to their offices. Make thoughtful trade‑offs between innovation and immediate customer requirements. Operate as a founding team member, wearing multiple hats and stepping outside your comfort zone. Adapt to rapidly shifting priorities in a startup environment. Help customers feel your impact every day. Qualifications & Experience Hands‑on experience architecting, designing, and implementing agentic AI systems. Strong experience building scalable agentic systems. Proficiency in at least one agentic framework and familiarity with other frameworks. Expertise in using, fine‑tuning, and integrating cutting‑edge LLMs into production systems. Proven track record in fast‑paced startup environments and collaborating with global teams. Expertise in React and either Python or Node.js. Solid knowledge of ML, AI, and LLM concepts. Strong people‑leadership experience and a bias for action. Ability to work on legacy code and communicate directly with customers. Willingness to commit to extended hours and deep focus. Company Values Customer‑First Outcomes – Every commit should trace back to resident or operator value. If it doesn’t solve a real problem, it doesn’t ship. Bias for Simplicity – We favor composable primitives over clever abstractions. Open standards, clean APIs, and clear contracts win over custom complexity. Quality Is a Gate, Not an After‑Thought – Quality is built in from day one. Our definition of done includes test coverage, performance checks, basic observability, and internal documentation. Data‑Driven Choices – 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). Instrumentation is lightweight but delivers meaningful signal. Transparency & Written Culture – Good ideas don’t expire in Zoom. We operate in public inside the company, using TDDs, PR reviews, and Linear tickets to tell the story. This keeps us async‑friendly, auditable, and aligned across time zones and functions. Benefits Great health insurance, dental, and vision. Gym and workspace stipends. Computer and workspace enhancements. Unlimited PTO. Company off‑sites with the team. Opportunity to play a critical role in building the foundations of the company and engineering culture. Significant equity in a venture‑backed company. #J-18808-Ljbffr Getzuma