AI Developer / Generative AI Engineer chez Cognizant

Job Title: AI Developer / Generative AI Engineer

Location: Zurich, Switzerland
Employment Type: Full time, 12 months contract with extension

Industry: banking

Role Overview

We 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 Responsibilities

• Design, 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 Experience

• Programming 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 Have

• Experience 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.