Agentic AI & Systems Engineer - Model-Based Engineering (MBD) - (M, F, NB)

ppbRandstad Digital /b, the specialized division of Randstad Italia focused on the search, selection, and training of ICT professionals, is looking for an bAgentic AI Expert for Model-Based Engineering (Pisa). /b /p pOur client is a global leader in telecommunications, enterprise solutions, and consumer electronics. As a pioneer in the industry, the company is committed to shaping the future of digital ecosystems through cloud computing, AI, and next-generation connectivity solutions. Its Research Center in Pisa plays a central role within the Group, focusing on advanced research into new technologies and applications in bdigital power and electric vehicles. /b /p pThe company is looking for an expert to expand its team in charge of developing next-generation Model-Based Design (MBD) tools. In this role, you will act as a Systems Engineer, enhancing the simulation, code generation, and diagram generation capabilities of existing tools through the integration of cutting-edge agentic AI technologies. You will join a dynamic, highly collaborative team of experts and PhDs passionate about research projects and innovative solutions. /p pbLocation /b: Pisa, Italy (On-site). /p pbSalary Range: /b Approx. €47,000 to €70,000 gross/year (commensurate with experience). /p h3Key Responsibilities /h3 pSupport the technological evolution of proprietary MBD tools toward AI-assistance, large-scale efficient simulation, and optimized code and test generation. /p pM.Sc. in Engineering, Computer Science, or a related field (PhD preferred). /p pExcellent knowledge of both Java and Python programming languages. /p pHands-on experience with AI frameworks (e.g., LangChain, LangGraph, Docling, PyTorch). /p pHands-on experience with AI coding agents (e.g., Claude Code, OpenCode, Codex). /p pExperience with the OpenAI API, MCP servers, and tool calling. /p pExperience with agentic patterns, prompt engineering, and Chain-of-Thought reasoning. /p pExperience in building efficient multi-agent AI architectures (including RAG, orchestration, and tool calling) and integrating them into existing products. /p pExpertise in analysis and performance optimization (e.g., latency, scalability, token efficiency) of complex distributed LLM pipelines. /p pFamiliarity with Model-Based Engineering concepts (e.g., UML, Simulink/Stateflow diagrams). /p pPractical know-how in software testing, especially regression testing. /p pExcellent communication skills, initiative, teamwork, and a product-oriented mindset. /p pFluency in English and the ability to work effectively in a multicultural environment. /p pAvailability for business trips in Europe and China. /p h3Nice to Have /h3 pExpertise in model-to-text, text-to-model, and model-to-model transformations. /p pExperience in reinforcement learning, model quantization, distillation, and fine-tuning. /p pRTOS or control/vehicle software development experience. /p pStrong knowledge of C++. /p pExperience with the Eclipse Modeling Framework (EMF). /p pExperience with MLOps, especially in setting up private LLM deployments with vLLM. /p pKnowledge of CI/CD frameworks. /p /p #J-18808-Ljbffr