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Staff Engineer AI Agents

About Zuma

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Zuma San Francisco, San Francisco Bay Area Source published Mar 17, 2026 Verified 9 hours ago
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EmploymentFull-Time

Overview

About Zuma

Full job description

About Zuma

Zuma is pioneering the future of agentic AI in property management. We build AI agents that act as property managers, handling the full spectrum of interactions with both prospects and current residents on behalf of our clients. Our agents don’t just assist human workflows; they own them end-to-end, operating across leasing, collections and resident communications. Zuma has ambitions to continue expanding into adjacent work activities in tangential areas of property management.

Our flagship product is a multichannel leasing agent, a fully autonomous AI that engages prospects over voice, text, and email, guiding them through the entire leasing journey without human intervention. Today we sell exclusively to large enterprise property managers and are trusted by some of the largest apartment operators in the country, including Blackstone’s residential portfolio, the largest apartment management group in the US. This is a ~$200B market that has been dramatically underserved by technology, and we’re rewriting the playbook.

Off the back of our Series A, Zuma is scaling rapidly. We’ve raised over $17M to date with backing from world-renowned investors including Andreessen Horowitz (a16z), Y Combinator, King River, Range Ventures, and distinguished angels like YC’s former COO, Qasar Younis.

Role at a Glance

This is a rare chance to shape the future of how an entire industry operates — not in theory, but in production, at scale, touching real customers and physical assets every day. At Zuma, human and AI agents work side by side, and you'll help define what that collaboration looks like at its best.

200,000+ apartment homes currently impacted — and growing. Your agents will make residents' lives meaningfully easier at scale. $100M+ in rent collected annually by agents you'll help build and improve — real economic impact at enterprise scale.

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

Shape the future of property management by designing the human + AI workflows that will define the industry standard for the next decade. Join an A+ team with a wide range of experience across AI, enterprise SaaS, and proptech — people who have built and scaled products before and are doing it again. Own and influence how Zuma approaches entirely new workflows as we expand beyond leasing into the full resident lifecycle. Learn and establish best practices for deploying agents in real business operations — systems that touch real customers, real money, and real physical assets. This is the hardest and most valuable kind of AI engineering there is.

Own E2E projects that cross all areas of software development including full stack web apps, agentic AI solutions across multiple work activities, extensive integrations with PMS and CRM systems, infrastructure, and internal tooling. Architect, build, and deploy production AI agents using modern agent frameworks, owning the full lifecycle from design to reliability in production. Define the technical patterns and standards for how software is built across the engineering org — you will be setting the playbook others follow. Strengthen our core systems — including our onboarding/configuration system, integration frameworks, and AI performance analytics infrastructure. Collaborate directly with the VPE and product leadership to translate product vision into delivery, making high-stakes technical trade-offs with confidence. Own system reliability, observability, and continuous improvement — defining how we measure, monitor, and iterate on our agents and web products in production. Work across the stack (backend services, LLM orchestration, integrations, data pipelines, frontends) to ship agents and products that are robust and scalable. Tame legacy code and lay down new foundations — patterns and architecture you create will be inherited by the engineers who come after you. Be a close partner to the product and operations teams, turning their domain needs into intelligent automated workflows without requiring domain expertise upfront.

5+ years of software engineering experience with a track record of working up and down the stack including distributed systems. Comfortable working on frontends, backends, infrastructure, and databases. You’ll deliver the solution regardless of what’s needed, no anticipation of handoff to a different specialist. Strong proficiency in Python and/or TypeScript — the languages of our stack. Ability to work across ambiguity and drive projects from problem definition through production deployment independently. Clear, direct communicator who can translate complex technical architectures for non-technical stakeholders. Experience designing and shipping AI solutions in production — not just prototypes. You've owned AI systems that real users depend on. Experience building reliable, observable systems: tracing, error handling, fallback strategies, monitoring, and testing. Remote friendly but needs to fully overlap with core working hours of 8am - 3pm Pacific Time.

Prior experience at a startup or high-growth company; comfort shipping fast and iterating in production. AWS experience with IaC (Terraform) and comfort working with infrastructure / dev ops Background in building self-serve platforms or integration infrastructure. Experience with workflow automation platforms or business process orchestration. Experience with telephony integrations (Twilio or similar) and building voice-capable agents or chatbots across text and voice channels. Familiarity with speech-to-text, text-to-speech, or real-time audio streaming pipelines in production AI systems. Classical ML experience — supervised/unsupervised learning, feature engineering, model training and evaluation outside of LLM contexts.

Python, TypeScript/Node.js OpenAI, Anthropic LangGraph, OpenAI Agents SDK, custom orchestration layers AWS, AWS ECS, PostgreSQL, Redis RealPage, Entrata, Yardi, and other property management systems

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