<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p>The AI Developer role focuses on designing and building agentic AI solutions, including AI agents, copilots and autonomous workflows, as</p><p>well as developing LLM-based applications using RAG, APIs and vector databases. The role covers the full AI delivery lifecycle :from data</p><p>ingestion and pipeline development through deployment, monitoring, performance optimisation and scalable production operations using</p><p>LLMOps / MLOps practices. What makes this role exciting is the opportunity to work on end-to-end AI systems that combine multi-step</p><p>reasoning, decision-making, enterprise integration and close collaboration with business and IT teams to deliver high-impact use cases.</p><p><br/></p><p><br/></p><p><strong>Key Responsibilitie</strong></p><ul><li>Design and build agentic AI solutions, including AI agents, copilots and autonomous workflows,that deliver measurable business value.</li><li>Develop LLM-based applications using RAG, APIs and vector databases.</li><li>Create end-to-end AI pipelines from data ingestion through deployment and monitoring.</li><li>Implement multi-step reasoning and decision-making systems to support intelligent AI workflows.</li><li>Apply LLMOps / MLOps practices to build scalable, reliable production systems.</li><li>Monitor and optimise performance across quality, latency, cost and hallucination-related dimensions.</li><li>Collaborate with business and IT teams to identify, shape and deliver high-impact AI use cases.</li><li>Stay current with advancements in agentic AI and the broader LLM ecosystem.</li></ul><p><br/></p><p><strong>.</strong></p><p><strong>Required Experien</strong></p><ul><li>· Strong experience in AI, machine learning or software engineering. · </li><li>Hands-on experience building and deploying LLM-based or agentic AI applications. · </li><li>Experience integrating AI systems with APIs, tools and enterprise platforms. ·</li><li>Familiarity with orchestration frameworks, such as LangChain or similar. · </li><li>Knowledge of MLOps / LLMOps practices and lifecycle management. · </li><li>Experience working with data platforms and large-scale datasets. · </li><li>Experience working in Agile, cross-functional environment</li></ul><p><br/></p><p><strong>Essential Technical Skills</strong></p><ul><li>· Strong Python programming skills and experience with AI frameworks, including Hugging Face and LangChain. · </li><li>Experience with LLMs, including prompt engineering, RAG, embeddings and vector databases. </li><li>Understanding of agentic architectures, including tool use, planning, memory and orchestration. · </li><li>Experience building APIs and integrating AI into applications and workflows. · </li><li>Familiarity with data architectures, including data lakes, lakehouses and SQL. · </li><li>Understanding of evaluation methods for AI systems, including quality, safety and performance. · </li><li>Strong problem-solving and communication skills. · </li><li>Fluent English; German language skills are a plus.</li></ul><p><br/></p><p><strong>Nice-to-Have Skills</strong></p><ul><li>German language skills. · </li><li>Exposure to similar orchestration frameworks beyond LangChain. ·</li><li>Broader experience with large-scale data platforms and enterprise AI integration patterns.</li></ul> </div>