Forward Deployed Engineer, Gtm, Dach

Notion Notion · Enterprise · Munich, Germany · Sales

Forward Deployed Engineer for Notion's Go-To-Market team in DACH, focusing on complex customer engineering engagements. This role involves leading large-scale migrations, integrating Notion with third-party systems, and deploying AI/agentic solutions. Responsibilities include hands-on technical delivery, acting as a trusted advisor, designing and operating custom agents and AI workflows, building data pipelines, and resolving complex challenges. The role also involves contributing to best practices and influencing the product roadmap through feedback loops.

What you'd actually do

  1. Own the hands-on technical delivery of customer engagements, including deep technical discovery, requirements gathering, solution design, and end to end implementation.
  2. Act as a trusted technical advisor, helping customers make informed architectural decisions and identify opportunities to expand and deepen their use of Notion.
  3. Design, build, and operate custom agents, integrations, automations, and data pipelines that connect Notion with customers’ systems and workflows.
  4. Lead the design and execution of large-scale content and data migrations, including discovery, scoping, data modeling, transformation logic, validation, and post-migration optimization.
  5. Work closely with client stakeholders to gather business and technical requirements and translate them into well-architected solutions that maximize the value of the Notion platform within their broader technical ecosystem.

Skills

Required

  • Proficiency in at least one programming language such as Java, JavaScript, Node.js, SQL, or Python
  • Hands-on experience with APIs and data integration
  • Strong written and verbal communication skills
  • Fluency in English and German

Nice to have

  • Experience working in SaaS professional services, preferably in a startup or high-growth environment.
  • Experience deploying AI agents autonomously in complex coding or business workflows.
  • Background in developing technical frameworks, discovery methodologies, or internal tooling from the ground up.
  • Strong history of collaboration with product and engineering teams, including influencing roadmaps or architectural decisions.
  • Experience supporting pre-sales or early engagement phases, including technical discovery, migration scoping, feasibility analysis, effort estimation, and building prototypes or custom scripts to validate approaches.
  • Strong track record of successful enterprise customer implementations.

What the JD emphasized

  • production AI/agentic deployments
  • design and deploy production-grade custom agents and AI workflows
  • customer-facing engineering role
  • writing production-quality code
  • Hands-on experience with APIs and data integration
  • track record of delivering customer value
  • Experience deploying AI agents autonomously in complex coding or business workflows

Other signals

  • production AI/agentic deployments
  • design and deploy production-grade custom agents and AI workflows
  • build foundational discovery frameworks, technical standards, and internal tooling