Serves as a technical leader responsible for spearheading the development of advanced artificial intelligence and generative AI solutions across the organization.

This role guides the strategic implementation of both traditional machine learning systems and cutting-edge generative models, translating business requirements into comprehensive technical architectures. The position entails mentoring junior team members while establishing best practices for AI/GenAI development, deployment, and monitoring.

The Senior Engineer architects end-to-end machine learning pipelines supporting both analytical and generative workloads, with particular emphasis on creating robust prompt engineering frameworks and evaluation methodologies for enterprise LLM applications. They conduct research on emerging AI/GenAI technologies, focusing on multimodal models and agent-based systems to drive innovation.

A crucial aspect of this role involves establishing appropriate guardrails and safety mechanisms for responsible generative AI deployment, while continuously optimizing model performance, scalability, and reliability in production environments. The Senior Engineer also communicates complex technical concepts to diverse stakeholders and contributes to strategic decisions regarding AI/GenAI technology adoption, ensuring adherence to ethical standards, security protocols, and regulatory compliance.

Mandatory

• 5+ years of professional experience across AI/GenAI/ML engineering roles, with 2+ years specifically in generative AI;
• Experience implementing GenAI throughout the software development lifecycle (code generation, documentation, testing);
• Strong theoretical understanding of both traditional machine learning and generative AI architectures;
• Advanced Python programming with extensive experience in TensorFlow, PyTorch, Keras, and LangChain;
• Expert-level prompt engineering experience with instruction-tuned LLMs and multimodal generative models;
• Advanced knowledge of retrieval-augmented generation (RAG) and fine-tuning methodologies for GenAI;
• Thorough understanding of both relational and vector databases for AI/GenAI applications.

Preferred

• Working knowledge of Java, C#, Go, or Node.js for integrating AI/GenAI capabilities across diverse codebases;
• Proven experience leading technical teams building combined AI/GenAI solutions;
• Excellent communication skills for explaining complex AI/GenAI concepts;
• Experience with CI/CD pipelines and MLOps practices for both traditional and generative AI;
• Track record of successful AI/GenAI project deliveries in production environments;
• Strong problem-solving abilities and analytical thinking.

Location: Milano, Roma, Torino, Pisa, Napoli, Treviso, Cosenza, Genova, Bari, Salerno, Bologna.