Director, Global Forward Deployed AI Programs

Job description

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 Portfolio Management Job Category: Professional All Job Posting Locations: Raritan, New Jersey, United States of America Job Description: We are searching for the best talent for Director, Global AI Forward Deployed Programs to be in Raritan, 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: The Director, Global AI Forward Deployed Programs will be part of the AI Strategy and Execution team in the Global Commercial Strategy Organization (GCSO). This leader will embed directly with Marketing, Medical Affairs, and Market Access teams at the Global level to build and ship production Generative AI and Agentic AI solutions that solve real business problems for our customers and J&J GCSO teams. This is a global leadership role that builds productized solutions for GCSO and influences regional AI teams with a strong bias toward action and impact orientation. The Director will set the technical and operational bar for every pilot and scaled AI solution across the Global commercial strategy organization and influence this for every region. They will stay close enough to the technical work in GCSO and in the regions, to review and align AI architectures, debug production issues, and pair with global and regional data scientists, data engineers and advanced analytics professionals. Their primary impact will come from the global standards they set, and the products they build. This leader will define key metrics of success for GCSO AI products from development to delivery and ensure coordination across regions on the development and delivery of AI products. You Will Be Responsible For: Capability Building & Leadership Build the Forward Deployed Engineering competency and influence without authority across GCSO and the regions. Partner with the regions, R&D and Supply Chain to  develop, and retain engineering talent with strong technical depth and business instincts across the enterprise. Provide technical standards, OKRs tied to business outcomes and AI adoption goals. Establish operating cadences such as standups, retrospectives, and engagement reviews that keep the team aligned. Partner with AI fluency leader to ensure technical skill building especially in the area of agentic AI for GCSO. Engagement Delivery & Technical Excellence Define AI use cases, scope work, and align success criteria before engagements begin. Define and monitor financial impact metrics such as token costs and ROI of AI products. Review technical architectures, harness designs, eval results, and code produced by the team or vendor partners. Ensure solutions are high-quality, measurably reliable, production-ready, and integrated into the AI ecosystem (eg Engagement.ai and Connext). Stay hands-on: lead technical discovery sessions, prototype solutions, and debug complex issues alongside the team and vendor partners. Ensure all solutions meet regulatory, privacy, ethical, and medical/legal/regulatory (MLR) standards, and partner with Technology, Privacy, and Compliance from design through deployment. Scale, Reuse & Influence Build repeatable playbooks, starter repositories, integration templates, and an internal knowledge base that capture what the team learns in the field. Partner with J&J Technology, Data Science, and Product teams to turn field insights into platform and product improvements. Serve as the voice of the business in AI planning and roadmap discussions. Support evaluation of external AI vendors, model providers, and enterprise platforms. Bring hands-on deployment experience to build-versus-buy decisions. Champion AI adoption across GCSO, and help business teams move from pilots to sustained use. Agent Harnesses, Evaluation & Production Deployment Define the team's standards for agent harnesses: orchestration patterns, tool and API integrations, context and memory management, guardrails, and human-in-the-loop checkpoints suited to a regulated commercial environment. Establish an evaluation discipline for every engagement. This includes task-specific eval sets built with business and MLR partners, automated regression suites, LLM-as-judge and human review workflows, and clear quality thresholds a solution must meet before release. Ensure evals run continuously, not just at launch, so model upgrades, prompt changes, and new data sources are tested against agreed benchmarks before reaching users. Own the path from prototype to production with Technology and platform teams, including CI/CD for AI applications, staged rollouts, versioning of prompts and models, and rollback plans. Put observability in place for deployed solutions: tracing, cost and latency monitoring, quality and drift tracking, and incident response. Make sure issues found in production feed back into evals and harness improvements. Build reusable harness components, eval frameworks, and deployment templates into the team's playbooks so each new engagement starts further ahead than the last. Qualifications / Requirements Education: Bachelor's degree in Computer Science, Engineering, Operations Research, or a related field, or equivalent experience, is required. Master's or PhD in a related field is preferred. Experience & Skills 7+ years of experience in software engineering, ML/AI engineering, solutions architecture, or a technical client-facing role such as forward deployed engineering or technical consulting. 5+ years of people management experience leading engineers in a delivery, services, or embedded/Forward Deployed Engineering-style organization, with a track record of hiring, developing, and retaining strong technical talent. Experience building the FDE capability from scratch. Hands-on experience shipping production LLM applications and AI agents, including RAG architectures, tool use, multi-step orchestration, and prompt engineering. Demonstrated experience designing and running LLM evaluations, such as building eval datasets, defining quality metrics, automated and human-in-the-loop review, and using results to make release decisions. Experience deploying and operating AI systems in production, including CI/CD, monitoring and observability, cost and latency management, and working within enterprise security, privacy, and compliance requirements. Experience working directly with business stakeholders on technical implementations, including comfort navigating complex organizational dynamics in a large enterprise. Executive presence, with the ability to move fluidly between strategic conversations with senior leaders and hands-on debugging sessions with engineers. Strong written and verbal communication skills, including the ability to translate technical complexity into clear narratives for d