Sr. Manager, Digital Solutions & AI

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.

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Job Description:

The Sr. Manager, Procurement Digital Solutions & AI will sit within the Procurement Digital Solutions & AI organization, and shape the solution bridge between global process objectives and AI-enabled capabilities. In partnership with the Global Process, Data, IT, and SAAS supplier stakeholders, this role is responsible for translating process objectives into high-level intelligent workflow designs, connecting data and intelligent capabilities across the internal & SAAS-based AI ecosystem, and across end-to-end Procurement to deliver cohesive, and scalable outcomes.

This position will also oversee & manage the delivery against AI roadmaps, ensuring milestones are met and work is executed with quality and discipline.  They will also ensure the on-going effectiveness of agentic-based solutions through both cost & value management.

Key Accountabilities

1) Intelligent End-to-End Workflow Solutioning — 40%

·        Define high-level solution patterns for intelligent workflows (end-to-end), including platforms / components, data integration points, orchestration approach, and experience flow.

·        Define how SaaS platform AI, internal AI agents/assistants, and an orchestration layer work together to deliver a cohesive human-centered experience.

·        Establish clear tradeoffs (build vs. buy vs. augment), aligning to feasibility, cost, risk, scalability, and Enterprise standards.

2) Agentic AI Capability Mapping — 40%

·        Map business requirements to the right AI approach (e.g., platform-native AI, internal agent, assistant, analytics/ML, document intelligence, retrieval-based knowledge).

·        Apply agentic AI principles: agents that plan, use tools, take actions, and execute multi-step workflows (vs. single-turn chat).

·        Recommend fit-for-purpose agentic design patterns (e.g., plan-and-execute, tool-use, reflection, human-in-the-loop checkpoints) to match process risk and automation goals.

·        Incorporate human-in-the-loop controls and escalation paths for high-stakes decisions and exception handling.

3) Delivery Leadership, Governance, and Adoption Enablement — 20%

·        Manage day-to-day execution oversight (ie. backlog planning; change & comms.); Ensure milestones/goals are met, and actively manage capacity, staffing needs, and delivery health.

·        Partner with process leaders, change, and comms. stakeholders to drive adoption and sustained value.

·        Actively manage agent run costs and value delivery, ensuring agent value is continuously optimized.

Required Qualifications

Education

·        Bachelor’s degree in Engineering, Data Science, Computer Science, Information Systems, or related field (or equivalent experience).

Experience

·        10+ years in a blend of business analysis, process engineering, product/solution design, intelligent automation, and / or AI solution delivery.

·        1–3+ years of people leadership and / or leading delivery pods as a first-line manager.

·        Experience designing and implementing:

• • Retrieval-augmented generation (RAG) and enterprise knowledge integration [
  • Agent orchestration/workflow layers
  • Output validation / guardrails, monitoring, and evaluation frameworks

·        Demonstrated experience translating business needs into solution intent, and delivery-ready requirements (including managing risks/assumptions/constraints).

·        Exposure to Procurement processes sufficient to connect opportunities to capabilities.

Core Skills

·        AI fluency:  Ability to select patterns for LLM/agentic workflows (tool use, memory / context, planning / reflection loops), and to define controls such as human review checkpoints.

·        Data Science fluency:  Understanding of foundational Data Science capabilities, and ability to apply that understanding to:

o   Conduct Data Science-based data analyses to support opportunity identification and business case development

o   Connect requirements to algorithmic data science, ML-based, GenAI-based, and Agentic-based capabilities for solution development

·        Requirements documentation, story writing / acceptance criteria, and stakeholder facilitation.

·        High-level solution design:  Components, integrations, orchestration thinking, and ability to communicate designs clearly.

Preferred Qualifications

• Experience with Procurement SaaS platforms, and connecting business requirements to platform capabilities (AI features included).
• Experience designing AI-ready data models, and semantic data layers.
• Hands-on experience designing and deploying intelligent solutions using the Microsoft ecosystem.

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