4+ years of experience leading engineering teams with a track record of shipping high-quality systems in a fast-paced environment
A technically leaning management style—you stay close to the code and the design, can credibly debate architecture and tradeoffs with senior ICs, and raise the technical bar of your team
Sufficient depth in search, retrieval, or large-scale data/indexing systems: lexical search (e.g. BM25), semantic search (embeddings, ANN/vector indexes), big data pipelines, hybrid retrieval, ranking, and the surrounding infrastructure
Experience product managing a platform or infrastructure scope: continuous evaluation technical architecture, SLAs, and a roadmap on behalf of internal customer teams, and making prioritization calls when those customers want different things
Strong systems judgment around scalability, performance, security, build vs buy and enterprise readiness—you've shipped systems that had to be fast, cheap, secure, and reliable at scale, not just functional
A bias for making hard tradeoffs to unblock product velocity while protecting the long-term health of the platform; comfortable saying "yes, with these constraints" or "no, here's the better path."
Experience working closely with product and AI teams as customers of a platform—you can speak both languages and translate between them
High tolerance for ambiguity and rapid change; you enjoy operating in a space where both the product surface (agents, AI) and the underlying technology (retrieval, LLMs) are evolving quickly
Experience building agentic or tool-using systems, or platforms that serve LLM-based products
Familiarity with permissioned, multi-tenant enterprise data—ACL-aware indexing, retrieval, and audit
Understanding of classic information retrieval metrics, ranking, or applied ML
Has led teams through rapid scope and priority changes and evolving org boundaries
A NOTE ON AI
You don’t need deep AI expertise for every role, but we do expect every Notino to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement — when that’s the case, we'll say so explicitly in the qualifications. People who thrive here don’t treat AI as a novelty. They use it to think better, and make their work easier for others to build on