Senior Scientist, AI Lead

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: Discovery & Pre-Clinical/Clinical Development Job Sub Function: Biotherapeutics R&D Job Category: Scientific/Technology All Job Posting Locations: Malvern, Pennsylvania, United States of America, Spring House, Pennsylvania, United States of America Job Description: 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 We are searching for the best talent for Senior Scientist, AI Lead to join our Cell and Gene Therapy Team located in Malvern, PA. Purpose: As an applied AI generalist, you will catalyst change by inspiring scientists and engineers to adopt innovative AI solutions and will play a critical role in shaping the future of our Cell and Gene R&D engine, ensuring we remain at the forefront of pharma development and AI integration. You use your strong scientific background in chemical engineering, biochemistry or related scientific fields to link scientific challenges, needs & opportunities across our development functions to cutting-edge AI solutions. As an AI solution lead, you start from the scientific challenge i.e. ‘the what’ and not the exact technical AI tooling on how to achieve “the how’. You navigate both internal and external AI networks & partners and you will be the driving force to innovate how we work and develop our Cell and Gene portfolio through AI. You have a broad understanding of the AI technology field such as Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Generative models, Expert Systems etc. and can relate this to fairness of data, data & information bias, explainability and the implications of autonomous decision-making We invite you to be a part in shaping and redefining the future of Cell and Gene therapy. You will be surrounded by passionate scientists & digital leaders and your contributions can truly make a difference! You will be responsible for: Lead and Deliver Applied AI Solutions Lead cross-functional AI projects supporting Cell & Gene Therapy development priorities. Define project scope, plans, resources, milestones, decision points, and measurable success criteria. Coordinate cross-functional teams and external partners; manage risks, dependencies, decisions, and stakeholder communication. Lead the design, prototype, test, and iteration of AI solutions across machine learning, generative and agentic AI, natural language processing, computer vision, knowledge graphs, predictive analytics, and AI-enabled digital twins. Evaluate solutions for model performance, scientific validity, usability, reliability, and business value. Integrate successful solutions into scientific workflows, data platforms, digital twins, and automated laboratory environments with reuse and scale in mind. Embed responsible AI and lifecycle practices, including fit-for-purpose validation, transparency, privacy, security, governance, human oversight, performance monitoring, and clear communication of model limitations. Translate Scientific Challenges into AI Use Cases Partner with process development, analytical, manufacturing, and business teams to identify scientific and operational challenges that could benefit from AI. Translate domain needs into clear AI use cases, user requirements, data needs, and expected outcomes. Assess use cases based on scientific value, business impact, data readiness, technical feasibility, risk, and scalability. Serve as a key interface between scientific subject matter experts, data science, and technology teams. Build Partnerships and Advance the AI Portfolio Establish productive relationships with internal data science teams, technology partners, academic collaborators, and vendors. Bring external developments and best practices into the organization while avoiding fragmented or duplicative solutions. Contribute to prioritization and evolution of the Cell & Gene Therapy AI roadmap. Drive Adoption and Measurable Impact Define and track adoption, scientific impact, cycle-time, quality, and efficiency measures. Share outcomes, lessons learned, and reusable practices to accelerate adoption across the organization. Promote a culture in which AI augments scientific expertise and accelerates learning while preserving appropriate human judgment. Qualifications: Required: A minimum of a BS degree in a core science or engineering field, including biology, chemistry, chemical/biochemical engineering, biomedical engineering, or a related discipline, with at least 4 years of relevant experience; OR an MS or equivalent with at least 2 years of relevant experience; OR a PhD or equivalent with 0-1 year of relevant experience is required. A minimum of 2 years of academic or industry experience delivering AI, machine learning, data science, or AI solution architecture initiatives. Experience applying these approaches to pharmaceutical or life sciences problems is preferred. Demonstrated experience leading complex projects from use-case definition through implementation. Working knowledge of multiple AI approaches, such as supervised and unsupervised learning, deep learning, generative AI, large language models, agentic AI, natural language processing, computer vision, knowledge graphs, reinforcement learning, or hybrid modeling. Ability to translate scientific questions into AI solution requirements and translate technical outputs into actionable scientific or business decisions. Strong interpersonal and communication skills, with the ability to influence diverse audiences. Strategic insight, strong personal leadership skills, detail oriented and a record of effective collaboration with diverse team me