Manager, Semantic Intelligence

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: Data Analytics & Computational Sciences Job Sub Function: Data Science Job Category: Scientific/Technology All Job Posting Locations: Titusville, New Jersey, United States of America Job Description: We are searching for the best talent for Manager, Semantic Intelligence to be in Titusville, NJ About Innovative Medicine Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow. Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way. Learn more at https://www.jnj.com/innovative-medicine Purpose: Johnson & Johnson Innovative Medicine Technology is seeking a Manager, Semantic Intelligence to lead the development of Semantic Intelligence within the J&J Innovative Medicine Technology team on the data platform and partner closely with the Global Commercial Strategy Organization (GCSO), business stakeholders, product teams, and technology teams. This is a technical leadership role responsible for translating complex business and data requirements into scalable platform solutions. Operating through a forward-deployed engineering model, the successful candidate will work directly with stakeholders and engineering teams to design, build, deploy, and support production-grade data and AI capabilities. The role requires strong experience in enterprise data products, cloud computing, data infrastructure, software engineering, and modern AI technologies, together with the ability to lead cross-functional delivery in a complex and regulated enterprise environment. You will be responsible for: Partnering with the Global Commercial Strategy Organization (GCSO) and other stakeholders to understand complex business and technical needs and translate them into scalable data and AI solutions. Leading the technical design, development, deployment, and ongoing enhancement of Semantic Intelligence capabilities on the data platform. Apply a forward-deployed engineering approach by working directly with users, product teams, architects, and engineers from problem definition through production adoption. Design and deliver reusable data products and platform capabilities that improve enterprise data accessibility, interoperability, and AI readiness. Provide technical leadership across cloud computing, data engineering, data infrastructure, APIs, metadata, semantic technologies, and AI-enabled applications. Collaborate with engineering, architecture, data science, product management, security, privacy, and governance teams to deliver secure, reliable, and scalable solutions. Establish and promote engineering standards for architecture, software development, testing, deployment, observability, documentation, and production support. Evaluate emerging data and AI technologies and recommend practical approaches aligned with enterprise architecture, security, privacy, compliance, and responsible AI requirements. Manage technical priorities, delivery plans, dependencies, risks, and stakeholder expectations across multiple initiatives. Mentor technical team members, oversee delivery partners, and contribute reusable engineering practices across the Johnson & Johnson Data and AI community. Qualifications / Requirements: Ph.D. with 2+ years of relevant industry experience, or M.S. with 5+ years of relevant industry experience, in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Information Systems, Computational Informatics, Engineering, or a related technical discipline. Significant experience designing, developing, and deploying enterprise-scale data products, cloud platforms, data infrastructure, analytics solutions, or AI-enabled applications in production environments. Experience with semantic modeling, enterprise metadata, knowledge graphs, graph data models, or comparable approaches that connect enterprise data with business context. Strong understanding of modern AI architectures, including large language models, retrieval-augmented generation, vector retrieval, semantic search, AI agents, orchestration frameworks, evaluation, monitoring, and responsible AI controls across cloud and open-source ecosystems. Experience in a forward-deployed engineering, solutions engineering, product engineering, or technology consulting role involving direct collaboration with end users. Experience delivering enterprise data platforms, semantic layers, AI-enabled data products, or knowledge management solutions at scale. Experience integrating AI capabilities into enterprise products, applications, and workflows using cloud-agnostic and open-source technologies. Strong experience with modern cloud and data platforms, including Snowflake, Amazon Web Services (AWS), Databricks, and related cloud-native services. Demonstrated experience across the data product lifecycle, including data ingestion, transformation, storage, modeling, APIs, metadata, governance, data quality, orchestration, observability, security, and operational support. Strong software engineering and technical delivery skills, including Python, SQL, distributed computing, source control, automated testing, CI/CD, containerization, and infrastructure automation. Experience designing and deploying reusable platform services and data products with defined interfaces, ownership, quality controls, documentation, service-level expectations, and production support. Demonstrated experience moving technical solutions from discovery and prototyping through architecture, engineering, production deployment, monitoring, and continuous improvement. Experience leading multidisciplinary technical teams and working across product management, architecture, engineering, data science, cybersecurity, privacy, and governance functions. Ability to diagnose complex technical and operational issues across application, data, integration, and infrastructure