Dir Technology Management

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Enterprise Management Job Sub Function: Technology Management Job Category: People Leader All Job Posting Locations: New Brunswick, New Jersey, United States of America, Palm Beach Gardens, Florida, United States of America, Raritan, New Jersey, United States of America, Raynham, Massachusetts, United States of America, Warsaw, Indiana, United States of America, West Chester, Pennsylvania, United States of America Job Description: DePuy Synthes is recruiting for a Director Technology Management, located in New Brunswick, NJ. Job Overview The Director Technology Management is responsible for leading the delivery and execution of enterprise Data Science and Artificial Intelligence initiatives across DePuy Synthes. Reporting to the VP, Chief Data and AI Officer, this role will partner closely with business leaders, product teams, data engineering, architecture, and digital organizations to identify, prioritize, develop, and scale AI and advanced analytics solutions that drive measurable business value. The successful candidate is a hands-on leader with strong technical expertise in machine learning, generative AI, agentic AI, and advanced analytics. This individual will lead a team of Forward Deployed Engineers (FDEs), Data Scientists, and AI practitioners , manage a portfolio of high-impact AI use cases, and serve as the operational lead for the Enterprise AI Governance Board , ensuring responsible, secure, and compliant AI adoption across the organization. Key Responsibilities Lead the execution of Data Science, Machine Learning, Generative AI, and Agentic AI initiatives across R&D, Supply Chain, Manufacturing, Quality, Commercial, and Corporate functions. Manage and mentor a team of Full-Stack Data Engineers (FDEs), Data Scientists, ML Engineers, and AI practitioners, fostering a culture of innovation, accountability, and continuous learning. Partner with business and functional leaders to identify, prioritize, and deliver high-value analytics and AI use cases aligned to enterprise objectives. Translate business challenges into scalable AI, machine learning, and advanced analytics solutions that drive measurable business outcomes. Lead the design, development, deployment, and operationalization of predictive, prescriptive, and generative AI solutions. Establish delivery roadmaps, success metrics, and value realization frameworks for Data Science and AI initiatives. Serve as the operational owner of the Enterprise AI Governance Board, coordinating governance processes, use case reviews, risk assessments, and approval workflows. Ensure AI solutions comply with enterprise governance standards, Responsible AI principles, model validation requirements, privacy expectations, and regulatory obligations. Collaborate with Enterprise Data, Architecture, Security, Privacy, Legal, and Quality teams to ensure AI solutions are scalable, secure, and compliant. Drive adoption of AI platform capabilities, reusable components, model development standards, and MLOps/LLMOps best practices. Establish and monitor AI model performance, accuracy, explainability, drift detection, and operational metrics. Provide technical leadership and guidance on machine learning algorithms, agentic AI architectures, LLMs, orchestration frameworks, vector databases, and AI application development. Partner with Data Engineering and Platform teams to enable scalable data foundations and modern AI capabilities on enterprise platforms. Evaluate emerging AI technologies, tools, frameworks, and vendors, providing recommendations for adoption and experimentation. Present program status, value realization, risks, and strategic recommendations to senior leadership and governance forums. Qualifications Education Bachelor’s degree required in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field. Master’s degree preferred. Experience and Skills Required 10&#43; years of relevant experience in Data Science, Artificial Intelligence, Machine Learning, Advanced Analytics, or related fields. Demonstrated experience leading Data Science, AI, or advanced analytics teams in a complex enterprise environment. Strong expertise across machine learning, deep learning, generative AI, large language models (LLMs), and agentic AI architectures. Hands-on experience building and deploying AI/ML solutions in production environments. Experience with MLOps, LLMOps, model lifecycle management, automation, and monitoring. Strong proficiency with modern AI and data platforms such as Databricks, AWS, Azure, SageMaker, vector databases, orchestration frameworks, and GenAI ecosystems. Experience partnering directly with business stakeholders to identify, prioritize, and deliver AI-driven business outcomes. Strong understanding of AI governance, Responsible AI practices, model risk management, explainability, and compliance requirements. Proven ability to lead cross-functional teams and manage complex AI and analytics programs. Strong communication and stakeholder management skills with the ability to influence technical and non-technical audiences. Experience managing globally distributed teams and working within matrixed organizations. Preferred Experience in healthcare, medical technology, life sciences, or other regulated industries. <