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United States
Remote only
We don't just use AI. We build with it, ship with it, and think with it. With a generous budget for tokens, our engineers use AI agents to write, review, and ship production code every day. We are building toward a world where humans design systems and AI builds them, and we are already far along that path.
We are hiring a hands-on Engineering Manager to lead Maps & Search. This team owns the home search experience across web and mobile. It's one of the most visible, highest-traffic surfaces–the search service alone handles a billion requests every month.
This is a role for a manager who leads from the front: someone who still lives in their terminal with AI, has strong opinions about how AI changes the SDLC, and wants to amplify what a small, senior, AI-augmented team can accomplish. You will set technical direction, stay close to the code, and help the team produce consistent impact.
Lead and grow the Maps & Search team. Own hiring, onboarding, coaching, 1:1s, direct feedback, and career development. Treat management as a craft and build a healthy, high-performing team that ships impactful changes.
Stay hands-on. Contribute directly — code and design reviews, architecture, thorny debugging— and stay technical enough to make smart calls on trade-offs.
Own and scale a high-throughput search platform. Drive the architecture, relevance, latency, and reliability of a real estate search system handling ~1B monthly requests and hundreds of millions of listings.
Deliver a world-class home search experience. Own the core home discovery experience across web and mobile — improving engagement, lead conversion, and agent workflows while keeping interactions fast and responsive at scale.
Push forward AI-powered discovery. Partner across teams to bring LLMs and intelligent ranking into search and user workflows, improving how buyers and agents discover, filter, and engage with listings.
Shape the roadmap with product and design. Define what we build and why, not just focusing on the how. Translate user needs and business goals into a clear technical plan, and own delivery end to end — planning, quality, reliability, and incident response.
You lead from the front. You're still close to the code and technically respected, and you treat management as a craft — growing engineers, giving clear feedback, and building a team that ships.
You already build with AI daily. You use AI as a core part of your workflow, not as a novelty — and you expect your team to as well.
You have strong opinions, loosely held, about how AI changes software architecture, team structure, and engineering culture.
You think in systems. You connect technical decisions to customer outcomes and business value.
You communicate clearly and directly. You can explain complex tradeoffs to product, design, and executive stakeholders.
You're energized by ambiguity and speed. You thrive in a fast-growing company where the roadmap evolves and ownership is real.
You like to have fun at work. We take our craft seriously, but we don't take ourselves too seriously. We celebrate wins, crack jokes, and genuinely enjoy building together.
8+ years of professional software engineering experience with meaningful senior or staff-level time, plus 2+ years managing engineering teams.
Search experience — you've worked on search, relevance, ranking, or retrieval systems. It doesn't have to be OpenSearch or Elasticsearch specifically, but you understand how search works and how to make it better.
Deep expertise in TypeScript, Node.js, and React, with the full-stack fluency to reason about the whole request path from UI to data.
Experience designing and operating scalable microservice architectures in cloud-native environments (AWS preferred).
Strong understanding of GraphQL, event-driven systems (Kafka), and databases (PostgreSQL, OpenSearch).
A proven track record operating high-traffic, low-latency production systems at scale — SLOs, incident response, and capacity planning are second nature.
Experience leading high-impact initiatives from concept through production in a SaaS environment.
Frontend: React, Tailwind, Apollo
Backend: Node.js / TypeScript microservices
Data: PostgreSQL, OpenSearch
Infrastructure: AWS, Kubernetes, Lambda
Messaging: Kafka, Redis