AI Strategy & Deployment Manager

Johnson & Johnson Innovative Medicine•Raynham, MA

1d•Hybrid

About The Position

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. Orthopedics Supply Chain is recruiting for an AI Strategy & Deployment Manager located in Raynham, MA, Raritan, NJ, West Chester, PA, Palm Beach Gardens, FL, Ireland and Switzerland. Candidates based in other DePuy Synthes locations will be considered as well. Johnson & Johnson announced plans to separate our Orthopedics business to establish a standalone orthopedics company, operating as DePuy Synthes. The process of the planned separation is anticipated to be completed within 18 to 24 months, subject to legal requirements, including consultation with works councils and other employee representative bodies, as may be required, regulatory approvals and other customary conditions and approvals. Should you accept this position, it is anticipated that, following conclusion of the transaction, you would be an employee of DePuy Synthes and your employment would be governed by DePuy Synthes employment processes, programs, policies, and benefit plans. In that case, details of any planned changes would be provided to you by DePuy Synthes at an appropriate time and subject to any necessary consultation processes. What's in it for you? Join a mission‑driven organization focused on delivering life‑changing Orthopaedics products to patients around the world. In this role, you will shape the enterprise AI strategy, define the technical vision, and lead the deployment of advanced AI systems that elevate supply chain performance and Keep People Moving. You’ll be at the center of transforming how the organization leverages AI—driving initiatives that range from machine learning to Agentic AI, while ensuring responsible AI adoption through strong governance, observability practices, and lifecycle management. This is an opportunity to join a company deeply investing in modern data foundations, committed to enterprise guidelines that keep us at the forefront of AI innovation in MedTech. If you're passionate about building meaningful AI solutions and influencing the future of healthcare, this is where you can make a real impact.

Requirements

Master’s Degree (or equivalent experience) or PhD in Computer Science, Engineering, Applied Mathematics, or related quantitative field.
6+ years of progressive experience in AI/ML, data science, or analytics, with proven success delivering enterprise production grade AI applications.
Expert proficiency in Python and SQL, with hands on experience using modern data engineering stacks, CI/CD, DevOps, and Git based workflows.
Strong foundational understanding of: Deep Learning, Transformer architectures, Attention mechanisms Reinforcement Learning with Human Feedback (RLHF) Model Context Protocol (MCP) Modern LLM and GenAI concepts
Experience with: Enterprise AI search platforms using Azure Cognitive Search and Azure OpenAI‑powered semantic ranking. Vector database implementations on Azure, including Azure AI Search Vector Store, PostgreSQL with pgvector on Azure Database for PostgreSQL, and integration with Azure Cosmos DB for vector embeddings. Azure OpenAI–based RAG (Retrieval‑Augmented Generation) and semantic retrieval pipelines, leveraging Azure Cognitive Search indexers, skillsets, and embedding models. LLM fine‑tuning and preference‑alignment techniques using Azure OpenAI (fine‑tuning APIs, safety evaluations, prompt engineering frameworks). Dataset creation, experiment management, and A/B testing using Azure Machine Learning (Azure ML) pipelines, MLFlow tracking, and Azure Monitor for evaluation. Classical ML model development and deployment (forecasting, predictive modeling, clustering) using Azure ML, AutoML, and MLOps on Azure DevOps/GitHub.
Ability to simplify complex Azure AI/ML concepts for business stakeholders, driving clarity, adoption, and strategic alignment.
Ability to simplify complex AI/ML concepts for business stakeholders, driving clarity and alignment.
Hands on experience building Agentic AI workflows or chatbots using frameworks like LangChain.

Nice To Haves

Knowledge of end‑to‑end supply chain processes—Planning, Manufacturing, Procurement, Distribution—preferably in MedTech or regulated industries.
Hands‑on experience with Infrastructure‑as‑Code (IaC), distributed and scalable data systems, or additional programming languages such as PySpark, Scala, or Julia.
Strong understanding of end‑to‑end supply chain processes—Planning, Manufacturing, Procurement, Distribution—preferably within MedTech, life sciences, or other regulated industries.
Working knowledge of enterprise platforms (ERP, MES, PLM) and experience navigating complex, fragmented data environments.
Demonstrated experience designing, building, and deploying Agentic AI applications tailored for MedTech or similarly regulated supply‑chain environments.
Ability to leverage AI, ML, and Agentic AI to optimize inventory levels, reduce working capital, minimize stockouts, and improve planning accuracy.
Experience developing AI‑driven strategies to enhance last‑mile service performance, including intelligent order allocation, proactive exception management, and dynamic fulfillment.
Proven ability to apply AI/ML to improve cash‑flow efficiency by optimizing demand signals, production sequencing, replenishment decisions, and inventory turns.
Practical knowledge of integrating AI agents with operational systems to autonomously trigger actions, orchestrate workflows, and provide real‑time decision support.
Publications or contributions to top-tier AI conferences (e.g., NeurIPS, AAAI, EMNLP, MICCAI).

Responsibilities

AI Strategy & Leadership Partner with cross‑functional supply chain leaders to define and execute the enterprise AI strategy—identifying high‑value opportunities, prioritizing use cases, and developing long‑term AI roadmaps that align with business objectives. Lead build vs. buy vs. wait analyses, evaluating cost, scalability, quality, timing, and strategic implications across low‑code, high‑code, and external solution options.
End-to-End AI Development & Deployment Own the end‑to‑end lifecycle for AI initiatives—from Agentic AI systems to classical ML—including data ingestion, feature engineering, model development, evaluation, and production deployment. Establish and enforce AI governance, MLOps, LLMOps, and observability frameworks, ensuring consistent quality, safety, reliability, and compliance across all AI assets.
AI Reliability, Observability & Automation Design and implement evaluation methodologies and observability strategies for GenAI and Agentic AI solutions. Develop a data flywheel that accelerates automation, continuous learning, and system optimization.
Business–Technology Partnership Translate complex Orthopaedics Supply Chain requirements into scalable, high‑value AI solutions. Work closely with product owners and business stakeholders to align solution design with operational goals and measurable outcomes.
Delivery & Program Management Manage AI project timelines, budgets, vendor engagements, resource planning, and delivery metrics to ensure timely, high‑quality execution. Track and communicate AI initiative performance, ensuring visibility and alignment across leadership teams.
Innovation & Continuous Improvement Stay up to date with advancements in AI, ML, data engineering, and Agentic AI—bringing forward recommendations and championing innovation. Promote best practices in AI reliability, model evaluation, governance, and responsible AI deployment.

Benefits

employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year