AI Enablement Engineer-Developer Experience

This role is located in Budapest, Hungary - We are a hybrid work environment and are in the office 3+ days/per 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, Israel and Japan.

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.”

You're a builder who's been inside the LLM/Agentic AI world, and you've turned that experience into tools that engineers rely on.

You think agentic AI and developers working together is one of the most interesting opportunities of this decade, and you want your fingerprints on the tools, standards, and platform that make that possible here.

You understand the full process of shipping an agent into production: prompting, tool and MCP design, reliability, evals, the UX of human-AI handoffs, and the plumbing in between.

• Partner with engineering teams to identify the highest-leverage AI opportunities in the developer workflow: from code generation and review to testing, debugging, and internal tooling.
• Build and maintain the internal agentic AI platform engineers rely on daily: skills, plugins, MCP servers, and integrations across our tech stack (source control, CI/CD, observability, ticketing, and more)
• Own foundational architecture and standards for how agents and model releases are evaluated, and deployed internally: including reliability, evals, efficiency, and secure tool access patterns