Enterprise Applied AI Lead

Role Summary

This is a strategic leadership role within the Data, Analytics & AI organization, focused on advancing Perrigo’s applied AI capabilities. The Applied AI Lead will be responsible for identifying, developing, and deploying AI solutions that drive business value across functions such as Brand & Category, Commercial, R&D, supply chain, marketing, and finance. This role reports directly to the VP – Data, Analytics & AI and will play a pivotal role in Perrigo’s digital transformation journey.

Responsibilities

• Define and execute the applied AI strategy aligned with Perrigo’s business goals.
• Identify high-impact AI use cases and lead cross-functional initiatives to deliver solutions.
• Collaborate with business leaders to prioritize AI projects and measure ROI.
• Define and execute a multi-year roadmap converging agentic AI, RPA, and process-mining.

• Lead the development and deployment of ML models and AI applications leveraging Gen AI, AI Agents, Agentic AI as well as AI/ML cloud services such as Azure ML.
• Operationalize an Agentic Automation CoE—governing standards, reusable templates, and ROI tracking.
• Ensure scalability, reliability, and ethical use of AI technologies.
• Oversee model lifecycle management including training, validation, monitoring, and retraining.

• Evaluate and implement AI platforms & tools (e.g., Azure ML, Databricks, Hugging Face).
• Architect modular multi-agent systems powered by frontier LLMs and leading agent frameworks (LangChain family, AutoGen, CrewAI, etc.).
• Drive automation and MLOps practices for efficient model deployment.
• Integrate AI solutions with enterprise systems and data platforms.

• Lead and mentor a team of data scientists, AI/ML engineers and AI Architects.
• Foster a culture of innovation, experimentation, and continuous learning.
• Promote agile methodologies and cross-functional collaboration.

• Ensure responsible AI practices including fairness, transparency, and privacy.
• Collaborate with legal and compliance teams to align AI initiatives with regulations.
• Establish governance frameworks for AI model usage and data handling.

Qualifications

• Technical Expertise: Proficiency in Python, TensorFlow, PyTorch, and cloud-native AI platforms.
• AI/ML Knowledge: Strong understanding of supervised, unsupervised, and reinforcement learning.
• Project Management: Proven ability to lead complex AI initiatives and deliver results.
• Communication: Excellent verbal and written communication skills, with the ability to influence stakeholders.
• Leadership: Demonstrated success in building and leading high-performing AI teams.
• Problem Solving: Strong analytical mindset with a focus on scalable solutions.
• These skills are typically acquired through the completion of a Bachelor's degree in computer science, data science, or closely related field; combined with 10–15 years of experience in AI/ML, with at least 3 years in a leadership role.
• 7+ years hands-on with Python, SQL, R, MATLAB, PyTorch, Keras, Git.
• 10+ years architecting ML/deep-learning solutions incl. LLMs (GPT-4, BERT, LLaMA, Dolly) and RAG pipelines.
• 8+ years building web apps (Dash, Streamlit, Shiny) and advanced data products.
• 8+ years implementing scalable AI/ML on platforms like Databricks with strong AI/MLOps. Deep knowledge of cloud data platforms (AWS, Azure) and compliance (GxP, HIPAA, GDPR).
• Masters or PhD preferred.

Education

• Bachelor’s degree in computer science, data science, or closely related field; advanced degree preferred.