Senior Forward Deployed Engineer (m/f/d)

About Blockbrain For mid-sized companies, knowledge is the last real competitive lever. Yet knowledge gets stuck in tools and SharePoint folders — or disappears when experts leave. While IT is still planning, employees are already using ChatGPT and the like — without governance, and sensitive data is leaking out. With the Knowledge Bots platform, Blockbrain creates what companies truly need: AI-powered knowledge management that is quick to implement, flexibly scales, and operates in a compliant manner. Teams use our GenAI building blocks to build tailored AI assistants, agents, and workflows in minutes — just like Lego. Series A funded with strong growth momentum (10x product usage & 5x revenue in 2025) Enterprise clients such as Roland Berger, Bosch, IONOS , and Harting from industries including manufacturing, finance, and legal — sectors with the highest security requirements ISO 27001 certified, EU AI Act ready. Made in Germany. Role & Responsibilities Forward Deployed Engineers are Blockbrain’s most client-proximate technical operators. Where Solutions Engineers sell and specify, FDEs ship — embedded directly in client environments to deploy, extend, and integrate the Blockbrain platform against real-world constraints. You own the gap between signed contract and working system. This is not a support role. FDEs write production-grade code, design integration architectures, and make technical decisions on-site with clients. You are accountable for time-to-value. Deploy & Integrate Own end-to-end delivery of Blockbrain in client environments — from infrastructure standup through agent configuration, retrieval tuning, and integration wiring Work directly with client engineering teams to ensure seamless adoption Build Client-Specific Extensions Develop custom connectors, API adapters, and workflow extensions using Blockbrain’s stack (TypeScript/Node.js, Python/FastAPI, Next.js) Tailor the platform to client data models, auth systems, and business processes Retrieval & Agent Tuning Configure and optimize Blockbrain’s knowledge retrieval layer — vector indexes, reranker pipelines, graph integrations — for client-specific environments Translate domain requirements into retrieval architecture decisions Infrastructure & Self-Hosted Deployments Support and troubleshoot Kubernetes-based deployments (Docker, ArgoCD), cloud integrations, and IaC (Terraform) Take full ownership of clients running self-hosted Blockbrain instances Surface Product Gaps Act as a direct signal channel from the field to Product and Engineering Document patterns, edge cases, and missing capabilities with enough specificity to become actionable backlog <p data-local-id="c350caea2384" data-prosemirror-content-type="node" data-prosemir