Sr Prin AI/Data Sci Engineer

Careers that change lives start here. Medtronic is a global leader in healthcare technology with a Mission to alleviate pain, restore health, and extend life. Our 95,000 employees work across more than 150 countries to put patients first — developing innovative medical technologies that improve the lives of 72+ million patients each year. Your unique talents will help shape the future of healthcare while building a career grounded in purpose, growth, and impact. A Day in the Life We are seeking a Senior Principal AI/Data Science Engineer specializing in Generative AI, Large Language Models (LLMs), Agentic AI, and Enterprise AI Platforms to lead the next generation of AI-enabled healthcare solutions. This role serves as the organization's technical authority for Generative AI, driving enterprise-wide AI strategy, architecture, innovation, governance, and deployment of scalable AI solutions across product engineering, clinical applications, digital health, quality, regulatory, and operational functions. The role requires deep expertise in Generative AI technologies and the ability to influence executive stakeholders, research teams, product organizations, and engineering functions to accelerate AI adoption while ensuring safety, compliance, explainability, and measurable business impact. A Day in the Life As a Senior Principal Generative AI SME, you will: Partner with executive leadership, R&D, product management, clinical experts, and software engineering organizations to define and execute enterprise Generative AI strategy. Serve as the technical lead for Generative AI initiatives spanning healthcare products, clinical decision support, software development lifecycle acceleration, regulatory automation, digital health, and operational transformation. Architect enterprise-scale AI platforms leveraging Large Language Models, Agentic AI systems, Retrieval-Augmented Generation (RAG), Knowledge Graphs, AI Agents, and multimodal foundation models. Drive AI innovation programs by identifying high-value opportunities where Generative AI can improve patient outcomes, engineering productivity, quality, and business efficiency. Define reference architectures, governance models, AI platform standards, design patterns, and reusable frameworks for enterprise adoption. Lead design reviews, architecture assessments, and technical evaluations of Generative AI solutions across business units. Collaborate with domain experts in Neuroscience, Cardiovascular, Medical Surgical and organizations to develop domain-specific AI solutions. Guide teams in fine-tuning foundation models and building healthcare-specific LLM solutions using enterprise and clinical datasets. Establish best practices for Prompt Engineering, AI Agents, RAG pipelines, semantic search, vector databases, AI observability, and model lifecycle management. Lead exploration of emerging technologies including Agentic AI, AI Copilots, Digital Twins, Knowledge Graph AI, Multimodal AI, and Autonomous Reasoning Systems. Drive implementation of AI governance frameworks addressing transparency, explainability, bias mitigation, risk management, security, and regulatory compliance. Mentor principal engineers, data scientists, AI engineers, and technical leaders while building organizational capability in Generative AI. Represent the organization in innovation councils, technical forums, conferences, research partnerships, and external collaborations. Partner with cloud, security, infrastructure, and platform engineering teams to enable scalable and secure AI deployments. Evaluate emerging LLMs, foundation models, open-source AI ecosystems, and AI tooling to establish enterprise AI roadmaps. Define and monitor AI success metrics, model quality measures, adoption KPIs, and business-impact indicators. Responsibilities may include the following and other duties may be assigned: AI Strategy & Innovation Define and drive enterprise Generative AI vision, strategy, roadmap, and adoption framework. Identify transformational AI opportunities across healthcare products, clinical workflows, software engineering, quality systems, and business operations. Lead AI innovation initiatives from concept through production deployment. Generative AI Architecture Architect scalable AI platforms supporting: Large Language Models (LLMs), Small Language Models (SLMs), Retrieval Augmented Generation (RAG), Agentic AI Systems, Multimodal AI Models, Knowledge Graph AI, AI Copilots, Autonomous Workflows, AI Orchestration Platforms Model Development & Fine-Tuning Lead adaptation and fine-tuning of foundation models for healthcare-specific use cases. Develop domain-specific AI solutions using enterprise, regulatory, engineering, and clinical knowledge. Establish enterprise standards for model benchmarking, evaluation, validation, and continuous improvement. Enterprise AI Platform Leadership Develop reusable AI frameworks, accelerators, and reference implementations. Define enterprise architecture standards for AI deployment, observability, governance, security, and compliance. Drive platform modernization using cloud-native AI architectures. AI Governance & Responsible AI Ensure AI solutions comply with healthcare regulations and enterprise governance requirements. Champion responsible AI principles including fairness, transparency, explainability, safety, traceability, and human oversight. Establish model monitoring, risk management, and AI audit readiness processes. Technical Leadership Serve as the highest-level technical authority for Generative AI initiatives. Conduct architecture reviews and technical assessments. Mentor engineering and AI teams globally. Influence technical direction across product portfolios and operating units. Required Knowledge and Experience B.E/B.Tech/Master's or PhD in: Computer Science/Artificial Intelligence/Machine Learning/Data Science/Computational Statistics/Applied Mathematics/Related quantitative discipline 15+ years of software engineering, AI, machine learning, or data science experience. 8+ years developing machine learning and AI systems. 5+ years specializing in Generative AI technologies. Demonstrated leadership in enterprise-scale AI transformation initiatives. Proven experience architecting and deploying production-grade AI platforms. Required Technical Expertise Generative AI & Foundation Models GPT Family, Llama Models, Mistral, Claude, Gemini, DeepSeek Med-PaLM, BioGPT, MedBERT, T5 Transformer Architectures Advanced AI Techniques Retrieval-Augmented Generation (RAG), GraphRAG, Knowledge Graphs Agentic AI, Multi-Agent Systems, Prompt Engineering, Fine-Tuning (SFT, PEFT, LoRA) Reinforcement Learning from Human Feedback (RLHF), Synthetic Data Generation, Multimodal AI AI Frameworks & Platforms PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, Copilot Studio, Azure AI Foundry Data Science & Analytics Python, NLP, Statistical Modeling, Feature Engineering, Model Evaluation, Data Pipelines, Experiment Tracking Cloud & MLOps Azure AI Services, AWS AI/ML Services, Google Vertex AI, Kubernetes, Docker, MLFlow, CI/CD for AI Systems, A