Agentic AI & Systems Engineer – Model- Engineering; MBD M, F, NB

Position: Agentic AI & Systems Engineer – Model-Based Engineering (MBD) - (M, F, NB)
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 (Pisa).

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. €47,000 to €70,000 gross/year (commensurate with experience).

Key Responsibilities:

Support the technological evolution of proprietary MBD tools toward AI-assistance, large-scale efficient simulation, and optimized code and test generation.
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., Lang Chain, Lang Graph, Docling, PyTorch).
Hands-on experience with AI coding agents (e.g., Claude Code, Open Code, 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.

Il presente annuncio è rivolto a persone di qualsiasi genere (F/M/NB) ai sensi della Legge n. 300/1970, dei

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