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Sr. Manager, Digital Solutions & AI

At Johnson & Johnson,we believe health is everything.

Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions 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:
Business Intelligence

Job Category:
Professional

All Job Posting Locations:
Bangalore, Karnataka, India

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 pa...




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