AI Developer / Generative AI Engineer

Job Title: AI Developer / Generative AI EngineerLocation: Zurich, SwitzerlandEmployment Type: Full time, 12 months contract with extensionIndustry: bankingRole OverviewWe are seeking experienced AI Developers with strong expertise in Python and hands-on experience building and deploying Generative AI solutions using LLMs, LangGraph, Neo4j, and multi-agent orchestration frameworks (MCP/A2A protocols). The ideal candidate should also have a solid foundation in traditional machine learning, data engineering, and cloud-based AI workflows.Key ResponsibilitiesDesign, develop, and deploy AI solutions leveraging Generative AI, LLMs, and multi-agent architectures.Build data pipelines, perform data preprocessing, and manage data transformations using SQL and other tools.Apply machine learning and deep learning techniques such as classification, clustering, and predictive modeling.Develop and integrate RAG (Retrieval-Augmented Generation) systems, prompt engineering, and vector database implementations.Collaborate with cross-functional teams to design scalable AI workflows and orchestration systems.Implement and maintain CI/CD pipelines, API integrations, and version control systems.Contribute to optimization of data analytics, model performance, and AI infrastructure.Required Skills And ExperienceProgramming Proficiency:Strong expertise in Python for AI/ML development.Proficiency with SQL, ETL design patterns, and data modeling techniques.Generative AI & LLM Development:Hands-on experience with GPT-based models, LangChain, LangGraph, and vector databases.Experience with RAG architectures and prompt engineering.Knowledge of multi-agent systems, AI orchestration, and MCP/A2A protocols.Machine Learning Expertise:Solid foundation in classification, clustering, regression, decision trees, and neural networks.Experience in predictive modeling and data mining.Data Engineering & Analytics:Experience in data preprocessing, transformation, and pipeline development.Strong analytical skills with ability to work with large datasets.Software Engineering Practices:Familiarity with APIs, RESTful web services, and data connectors.Experience with GitLab (or similar version control systems) and CI/CD pipelines.Nice to HaveExperience with Azure Cloud and related technologies:Azure Data Lake Storage (ADLS), Databricks, Azure Data Factory.Knowledge of Big Data analytics on Azure or on-premises environments.