Staff Software Engineer, Backend

About Genius AI Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more. Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points. About the Role Genius AI is building 0-to-1 AI products we expect to be a massive revenue driver, and this role sits at the center of that build. As a Staff Backend Engineer, you'll be the technical anchor for our highest-innovation teams: setting architectural direction, validating options through proof-of-concepts, and turning ambitious initiatives into clear, buildable roadmaps. This is an IC role with real leadership weight, roughly 60% architecture, planning, and technical direction, 40% hands-on building. The person in this role will be a force multiplier: unblocking engineers before they know they're stuck, making the hardest technical calls so the team doesn't lose momentum, and setting a new standard for what great backend engineering looks like at Genius AI. You won't be maintaining systems someone else designed, you'll be raising the ceiling on what th [... source excerpt omitted ...] mutable to our NYC headquarters and will operate in a hybrid environment. We default to being in-office 3–4 days per week with required attendance on Tuesdays and Thursdays. What You'll Do Architect and own the technical direction of AI-powered products and 0-to-1 builds, weighing long-term trade-offs with precision and keeping a healthy backlog of forward-looking, build-ready work Integrate AI models and LLMs into customer-facing products, not as experiments, but as production systems with real reliability and performance requirements Shape how Genius AI builds with AI, your architectural decisions will define what's possible across the product for years Write high-qualit [... source excerpt omitted ...] f owning system design and architectural choices for high-scale or high-growth products Already building with AI as a structural part of how you work, you've integrated LLMs into production systems, used AI tooling to accelerate your development workflow, and have a sharp point of view on where AI changes what's architecturally possible Ship fast and course-correct, you're comfortable making architectural calls with incomplete information, iterating rapidly in production, and treating ambiguity as a feature of early-stage work, not a reason to slow down Deep Kotlin expertise with strong intuitions about backend architecture, service design, and performance at scale (TypeScript e