Descrizione dell’offerta di lavoro📌 About the Position We are seeking a forward-thinking AI Developer to design, implement, and scale autonomous, goal-driven AI systems capable of decision-making, multi-step planning, collaboration, and continuous improvement. This role is ideal for someone passionate about AI solutions/architectures, prompt engineering, and modular AI workflow orchestration, with hands-on experience building production-ready AI agents that interact with tools, data, and real-world systems. Although the role is remote-first , the position requires a few mandatory in-office days per month in Basel (Switzerland) 🔧 Requirements (Must-Have) 3+ years of experience in software development or applied AI. Strong Python proficiency with experience in agent frameworks such as LangChain, DSPy, AutoGen, CrewAI, or equivalent systems. Deep understanding of agent design patterns, including planner/executor, memory/reflection loops, tool selection, and self-evaluation. Expertise in prompt engineering, including chain-of-thought, ReAct, structured prompting, and output validation. Experience building RAG systems, including chunking strategies, embedding optimization, and retrieval tuning. Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, OpenSearch). Experience deploying and integrating LLMs via APIs (OpenAI, Anthropic, Cohere) and open-source models (LLaMA, Mistral, Qwen, DeepSeek). Familiarity with LLM serving and inference frameworks such as vLLM, TGI, or Ollama. Experience with tool integration, including REST APIs, file systems, databases, and browser automation. Solid understanding of Docker, Git, and basic cloud infrastructure (AWS, GCP, Azure). Strong command (B2-C1) in English and German. 📓Key Responsibilities Architect and build agentic AI systems using frameworks such as LangChain, AutoGen, DSPy, CrewAI, or custom-built orchestration tools. Design modular, goal-oriented workflows enabling autonomous agents to plan tasks, collaborate with other agents, and interact with external tools. Implement planner–executor, ReAct, reflection, and self-verification agent patterns. Develop advanced prompting strategies, including chain-of-thought, tree-ofthought, structured outputs, and prompt versioning. Build and integrate memory systems (short-term, long-term, episodic) to support context persistence and learning. Integrate LLMs (OpenAI, Anthropic, Mistral, Cohere, DeepSeek, opensource models) with execution environments such as Python, Bash, SQL, REST APIs, and browser automation tools. Implement tool calling / function, API orchestration, and code execution agents. Design and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and hybrid search. Optimize agent performance for latency, reliability, cost efficiency, and scalability in real-world applications such as research agents, coding copilots, and planning assistants. Deploy and maintain agentic systems in production using Docker, CI/CD pipelines, and cloud infrastructure. Monitor agent behavior, log execution traces and reasoning steps (where appropriate), and continuously improve system robustness and alignment. Collaborate closely with data scientists, software engineers, product teams, and UX designers to deliver high-impact AI solutions. Implement human-in-the-loop workflows for oversight, feedback, and safe autonomy. 🎁 What We Offer Permanent contract with our client in Switzerland (or freelance option) Competitive salary package Flexible working model Attractive social benefits & company perks Work alongside cutting-edge AI. A culture that encourages autonomy, technical ownership, and continuous innovation Follow us to stay up to date with the latest news -> knowmad mood
