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Forward Deployed Engineer
CleraBerlin6 days ago
Full-timeVia ArbeitnowEngineering
Apply now About this role
About the Role We're a fast-growing enterprise AI solutions company building production-grade Generative AI applications that drive measurable impact for our clients across industries including Private Equity, Healthcare, Manufacturing, and Ecommerce. Our team of 20+ AI engineers delivers end-to-end AI transformation — from strategy to deployment — with a focus on clean architecture and tangible results. We're looking for a Forward Deployed Engineer to operate at the intersection of engineering, product, and customer success. You'll design and ship full-stack AI workflows in ambiguous, high-stakes environments — often embedded directly with client or operations teams. This is a high-ownership, high-impact role for engineers who love working close to the customer. What You'll Do Design and implement full-stack AI applications — from UI to API to orchestration logic. Rapidly build and deploy functional prototypes to test ideas and drive immediate value for clients. Work hands-on with internal and external stakeholders to shape requirements and debug problems in real-time. Own the technical delivery of custom solutions, integrations, and workflow automation end-to-end. Collaborate closely with AI, product, and design teams to iterate on user-centric features. Contribute to a growing internal toolkit of reusable components, design patterns, and best practices for GenAI systems. What We're Looking For Required: Strong CS fundamentals and a track record of end-to-end ownership of AI-powered workflows in production environments. Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines with vector databases. Proficiency building and deploying production-grade AI applications using OpenAI APIs and LangChain. Hands-on experience with a modern frontend stack: Next.js, React, TypeScript, and Tailwind CSS. Experience deploying on cloud platforms (Azure, AWS, and/or GCP) and managing scalable AI workloads. Solid production-grade testing, monitoring, an