Lead - Ai Engineering, Automation & Digital Transformation
Pubblicato il 02-10-2026 - Altro in Roma
Lead - AI Engineering, Automation & Digital Transformation Azienda : Americana Foods Ltd Tipo Lavoro : Tempo pieno Italy
Descrizione Lavoro - Lead - AI Engineering, Automation & Digital Transformation We are seeking a visionary and hands-on Lead - AI Engineering, Automation & Digital Transformation to drive enterprise-wide AI adoption, intelligent automation, and digital transformation initiatives from strategy through execution. This role demands a seasoned leader with deep expertise in AI/ML engineering, agentic AI, and process automation, with proven experience in transforming business operations and managing high-performing teams. The ideal candidate will work closely with CxO's office, GM IT and Senior Directors and business teams to embed AI-driven decision-making, operational efficiency, and innovation across the organization.
DESCRIPTION:
Lead and manage a cross-functional team of AI engineers, automation developers, and digital transformation specialists, fostering technical excellence and collaboration.
Architect, implement,
and scale AI/ML solutions and agentic AI platforms using Azure OpenAI, AWS Bedrock, Databricks, and modern LLM frameworks.
Design and deploy intelligent automation solutions (RPA, workflow orchestration, document intelligence) using platforms such as Power Automate, UiPath, and Azure AI services.
Build, fine-tune, and operationalize machine learning and GenAI models - including forecasting, recommendation, NLP, and computer vision use cases - with robust MLOps practices.
Drive the digital transformation roadmap: identify high-impact use cases, build business cases, and deliver measurable ROI through AI and automation initiatives.
Establish and enforce Responsible AI and governance practices including model documentation, bias monitoring, explainability, security, and access controls.
Collaborate with stakeholders to translate business needs into AI-powered solutions, reengineering processes end-to-end rather than automating inefficiencie