Senior Manager, AI Enablement
Listed on 2026-05-30
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IT/Tech
AI Engineer (Applied/Software), Data Analyst, Business Systems/ Tech Analyst, Data Science Manager
Job Overview
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 Med Tech 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.
Johnson & Johnson Innovative Medicine Technology is recruiting for a Senior Manager, AI Enablement. The primary location is Titusville, NJ, with consideration given to Horsham, PA. This role may require up to 10% domestic and international travel.
PurposeJohnson & Johnson Innovative Medicine Technology seeks a technologist with strong artificial intelligence experience to support the safe, scalable adoption of AI—including generative and agentic AI—across North American commercial teams. As Senior Manager, AI Enablement we will play a critical role in realizing strategic NA Commercial priorities through the power of AI, translating key opportunities into well‑articulated problem statements, requirements, and success criteria, partnering with the AI platform team to deliver fit‑for‑purpose solutions with measurable business impact.
We will serve as a bridge between product, platform, and AI teams working seamlessly with business stakeholders—beginning with CRM and Patient Experience—using product management and design thinking practices to define clear problem statements, validate value propositions, and establish KPIs/OKRs that demonstrate value realization.
Execute the AI enablement strategy by partnering with product, data, and AI platform teams to translate business priorities into clear problem statements, user needs, and outcome hypotheses, with explicit value propositions and measurable KPIs/OKRs. Serve as the day‑to‑day bridge between business stakeholders and Product, Data, AI Engineering, Data Sciences, and other business teams, applying Product Management and Design Thinking principles to define clear problem statements, validate value propositions, and ensure business requirements are faithfully translated for AI delivery teams.
Enable adoption and operationalization by partnering on change management (communications, training, UAT, rollout plans) and coordinating run‑state handoffs; contribute business context and stakeholder requirements to build‑vs‑buy evaluations; support vendor engagement by articulating business needs and success criteria. Manage governance for a subset of AI demand by establishing structure for intake, triage, and prioritization (e.g., strategic alignment, value vs. effort, readiness, risk/compliance), surfacing business requirements and constraints that inform build/buy/partner decisions.
Maintain a transparent backlog and communicate status, decisions, and outcomes for all stakeholders. Ensure responsible, compliant delivery by embedding privacy, security, legal/compliance, and responsible AI controls into requirements, testing, documentation, and launch readiness (e.g., human‑in‑the‑loop, monitoring, auditability, go/no‑go criteria). Operate with agile delivery disciplines (backlog refinement, sprint planning, demos, retrospectives) and contribute to team capability building by mentoring teammates, documenting playbooks, and continuously improving ways of working.
Apply product management and design thinking practices (empathize/define/ideate/prototype/test) to validate use cases, define MVPs, and instrument solutions so value realization can be measured and reported against agreed KPIs. Drive scale by identifying reuse opportunities (data access, evaluations, prompt/workflow templates, integration approaches) across commercial functions and partnering with the AI platform team to ensure solutions are positioned for cross‑portfolio leverage.
Education:
Bachelor’s degree required; advanced degree preferred in Computer Science, Data Science, AI/ML, Business, Engineering, or related field.
Experience:
10+ years…
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