Physical and Generative AI Engineer
Pubblicato il 02-10-2026 - Allergan in Italia
Company Description
About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
AbbVie is seeking a talented and hands-on AI Engineer to join our Strategy & Transformation function. In this role, you will be at the forefront of AI innovation, working directly with cutting-edge large language models (LLMs) and emerging AI technologies to develop solutions that transform how we operate.
We're looking for someone with a genuine passion for artificial intelligence, with strong technical fundamentals, and an attitude to proactively explore new possibilities. You'll move beyond theoretical knowledge to build working prototypes,
conduct rigorous experimentation, and collaborate closely with business stakeholders to drive meaningful AI adoption across the organization.
This is an excellent opportunity for someone who thrives in a dynamic environment, values intellectual curiosity, and wants to make a tangible impact on a global scale.
Job Key Responsibilities
- Solutions Development & Integration: Design, develop, and deploy applications leveraging large language models (LLMs) and generative AI technologies to solve business challenges that are practical and applicable to the site, whilst collaborating closely with the global Operations transformation functions
- Prompt Engineering: Craft, test, and optimize prompts to maximize model performance; develop prompt engineering strategies that balance accuracy, efficiency, and user experience
- Code Development: Write clean, maintainable, and well-documented code following best