Platform Engineer

This role is located in Budapest, Hungary. We are a hybrid work environment and are in the office 3+ days/week. Tulip, the leader in AI-native frontline operations, is helping companies around the world equip their workforce with composable, connected apps, leading to higher quality work, improved efficiency, and end-to-end traceability across operations. Tulip's cloud-native, no-code platform, powered by embedded AI, is driving the digital transformation of industrial environments through composable, human-centric solutions that go beyond disrupting the Manufacturing Execution System (MES) category. A spinoff out of MIT, Tulip is headquartered in Somerville, MA, with offices in Germany, Hungary, Singapore, and Israel. Tulip has been recognized as a World Economic Forum Global Innovator, a 2024 Deloitte Technology Fast award winner, one of Energage's Top Workplaces USA, and one of Built In Boston's "Best Places to Work" and "Best Midsize Places to Work." About You You are a platform engineer who likes to work close to the domain. Embedded with the Ecosystem team, you design the systems that turn their expertise into infrastructure the company and our customers can build on. The team brings years of manufacturing and operations knowledge, already expressed in working code, content, and tooling. Your role is to elevate that foundation into a coherent, AI-ready knowledge system that both AI agents and human builders can consume. In parallel, you bring production discipline to the tooling the team relies on, scaling it with clean APIs, durable data models, and reliable cloud infrastructure. This is a foundational design role on a team with strong builders and a clear mission. The next phase of value comes from architecting the underlying systems together. What Skills Do I Need? 3+ years of professional backend experience and solid REST/HTTP API design instincts Comfort with the full lifecycle of a production service: schema design, deployment, observability, and ownership of what you ship Production experience on AWS (or equivalent cloud). Comfortable deploying and operating services with common building blocks such as compute, containers, kubernetes, managed data stores, IAM, and networking, and working within infrastructure-as-code patterns Hands-on experience integrating LLMs (Claude, OpenAI, or equivalents) into real applications. Prompt engineering, RAG, structured outputs, and basic agent orchestration are familiar territory Strong instincts for what to build vs. what to glue together. You reach for boring infrastructure when it is the right answer and for novel patterns only when it earns its keep Genuine curiosity for the work of the people you build for. You want to understand the domain, not just abstract it Excellent English communication. You can write a clear design doc, push back on scope in a meeting, and explain a system to a non-engineer Nice to have: Working knowledge of evaluation frameworks for LLM systems Nice to have: exposure to industrial software, manufacturing, or any domain where the people closest to the problem are not engineers Relevant degree in Computer Science, Software Engineering, or equivalent working experience Key Responsibilities Embed with the Ecosystem team to learn the domain, the existing tooling, and the patterns the team has already proven. You will spend real time understanding what works before deciding what to extend Partner with engineers, solution builders, and content owners to translate their manufacturing and operations knowledge into structured, AI-ingestible skills, structured content, retrieval indexes, and the progressive-disclosure scaffolding that makes large knowledge surfaces usable by both agents and humans Architect and build the production backbone: APIs, services, retrieval pipelines, and the eval harnesses that keep AI-driven features honest as they evolve Take the tooling the team relies on today and grow it into systems built for scale. Cleaner contracts, sturdier