Senior Ai Systems Engineer - Agentic Ai & Model-Based Design
Pubblicato il 13-09-2026 - Randstad Technologies Talent Academies in Pisa
Functieomschrijving
Randstad Digital, the specialized division of Randstad Italia focused on the search, selection, and training of ICT professionals, is looking for an
Agentic AI Expert for Model-Based Engineering
.
Our 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 digital power and electric vehicles.
The 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.
Location:
Pisa, Italy (On-site).
Contract:
via Randstad Italia SpA.
Salary Range:
Approx. ****** to ****** gross/year (commensurate with experience).
Responsabilità
Key Responsibilities:
Support the technological evolution of proprietary MBD tools toward AI-assistance, large-scale efficient simulation, and optimized code and test generation.
Functie-eisen
M.Sc. in Engineering, Computer Science, or a related field (PhD preferred).
Excellent knowledge of both
Java and Python
programming languages.
Hands-on experience with AI frameworks (e.g., LangChain, LangGraph, Docling, PyTorch).
Hands-on experience with AI coding agents (e.g.,
Claude Code, OpenCode, Codex).
Experience with the OpenAI API, MCP servers, and tool calling.
Experience
with
agentic patterns, prompt engineering, and Chain-of-Thought reasoning.
Experience in building efficient multi-agent AI architectures (including RAG, orchestration, and tool calling) and integrating them into existing products.
Expertise in analysis and performance optimization (e.g., latency, scalability, token efficiency) of complex distributed LLM pipelines.
Familiarity with Model-Based Engineering concepts (e.g., UML, Simulink/Stateflow diagrams).
Practical know-how
in
software testing, especially regression testing.
Excellent communication skills, initiative, teamwork, and a product-oriented mindset.
Fluency in English and the ability to work effectively in a multicultural environment.
Availability for business trips in Europe and China.
Nice to Have:
Expertise in model-to-text, text-to-model, and model-to-model transformations.
Experience in reinforcement learning, model quantization, distillation, and fine-tuning.
RTOS or control/vehicle software development experience.
Strong knowledge of C++.
Experience with the Eclipse Modeling Framework (EMF).
Experience with MLOps, especially in setting up private LLM deployments with vLLM.
Knowledge of CI/CD frameworks.
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