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# Full-Stack Engineer

- **Company:** Orcrist Intelligence Platform (oip)
- **Location:** Berlin, Germany (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Data Integration, Python (Programming Language), PostgreSQL, Node.Js, Next.js, TypeScript, Web Applications, WebSocket, WebRTC, ReactJS, Kubernetes, Apache Kafka, Machine Learning Operations
- **Published:** September 5, 2026
- **Apply:** https://startup.jobs/full-stack-engineer-typescript-prototyping-orcrist-technologies-7912381

## About the Role

* 3+ years building production web applications and APIs in TypeScript (React/Next.js + Node).
 * Strong product-engineering instincts: you can turn ambiguity into a tight 1-3 week prototype scope.
 * Practical API and data-layer skills (PostgreSQL; comfortable integrating search when needed).
 * Comfortable working in Kubernetes/GitOps environments and maintaining good engineering hygiene (tests, CI, docs).
 * Security-conscious: you treat access control, privacy/PII handling, and audit expectations as part of "done."
 * Eligible to work in Germany; EU/NATO citizenship preferred for export-controlled projects.

Nice-to-haves

 * Real-time UI experience (WebSockets/WebRTC, collaborative editing, CRDT/OT).
 * Complex visualization experience (graph/geospatial UX; Cytoscape/D3/Mapbox/Cesium).
 * Some Python comfort for quick data/ML integration.
 * German language (B1+) and/or experience with regulated or mission-critical systems.

## Description

Build validated prototypes-not throwaway demos. As a Full-Stack Engineer on Innovation, you'll ship thin vertical slices end-to-end (UI + APIs + data integrations), then package your work so a delivery team can productize it confidently., * Prototype thin vertical slices across React/Next.js UI, Node.js APIs, and supporting storage/search integrations.

 * Collaborate with PM & Design in time-boxed discovery cycles: iterate quickly, demo often, and validate assumptions.
 * Align prototypes with shared primitives and standards: feature flags, auth flows, auditability, multitenancy assumptions, and basic observability.
 * Integrate workflows touching streaming/orchestration (Kafka/Temporal) and partner with Data/ML engineers when needed.
 * Ship an adoption package: documentation, interfaces, schemas, and an integration backlog that reduces handoff friction.


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