Sr Manager, AI Solutions

At Johnson & Johnsonwe believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented treated and curedwhere treatments are smarter and less invasive andsolutions are 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 more at .

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.

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Job Description:

The APAC Business Technology Team within Johnson & Johnson Innovative Medicine is looking for an extraordinary GenAI and Machine Learning Engineering Manager who is passionate about crafting developing and fielding data science solutions that drive impact for HCP (Health Care Professional) and patients.

Specifically we are looking for

A senior hands-on leader to build and scale production-grade full-stack GenAI solutions with a strong emphasis on backend systems data and AI/ML engineering. This role is expected to operate as a true partner to Business leaders- co-framing problems influencing solution strategy and co-owning measurable user and business outcomes - not as an execution-only engineering function.

Responsibilities

Product & Business Partnership

• Co-own problem discovery with Product/Business: translate objectives into well-defined testable problem statements user journeys and technical hypotheses.

• Challenge assumptions and requirements using user insights data realities feasibility constraints and system impact; recommend alternatives when they better achieve outcomes.

• Define and track success metrics and drive iteration when targets arent met.

• Communicate clearly with executive business and engineering audiences - articulating trade-offs decisions and rationale.

Solution Leadership

• Lead end-to-end solution for GenAI products: APIs services data pipelines orchestration LLM integration retrieval tool-calling and UI/UX touchpoints as needed.

• Make disciplined architectural trade-offs across performance reliability cost extensibility maintainability and time-to-value.

• Design for enterprise realities: identity/access data residency compliance constraints multi-environment deployments and integration with core systems.

• Drive platform thinking: prioritize reusable components (libraries templates shared services) over one-off builds.

Agentic & Full-Stack GenAI Applications

• Build and scale agentic GenAI applications that solve multi-step workflows on cloud platforms such as AWS and Azure.

• Define and implementrobust LLM patterns(prompting RAG tool orchestration validation and evaluation).

• ImplementLLMOps and lifecycle governancefor models and prompts including versioning evaluation and monitoring.

• Ensure solutions meetenterprise standardsfor quality reliability latency and cost.

• Embed Responsible AI security and compliance by design partnering with Risk Legal and Security.

Engineering Excellence & DevOps

• Provide hands-on leadership across the SDLC: design reviews coding standards testing strategy code reviews security reviews and operational readiness.

• Establishrobust CI/CD and standardized environmentsfor services and AI components utilizing cloud services.

• Ensureoperational excellencethrough observability incident management reliability practices and cost optimization.

Research and Innovation:

• Stay current with the latest advancements in Generative AI cloud technologies and ML/LLMOps practices and proactively translate relevant insights into team and platform adoption.

• Evaluate emerging tools techniques and methodologies to enhance GenAI capabilities developer productivity and operational efficiency integrating them into platforms and solutions where they add value.

• Lead targeted experimentation and proofs of concept scaling successful ideas into robust production-ready solution

Required Knowledge Skills and Abilities:

• Strong leadership skill with ability to influence the thought process and drive alignment.

• Proven track record in designing and building GenAI solutions with a strong expertise in prompt engineering LlamaIndex Langchain RAG Agentic AI workflow Knowledge graph AI red teaming libraries LLM monitoring and evaluation.

• Over 7 years of experience in the software development lifecycle as a developer with a focus on writing production code.

• Must have hands-on experience working with software development toolkits and devOps automation like Kubernetes Airflow Jenkins Jira Confluence and Git.

• Excellent programming skills in Python and proficiency in PySpark.

• Experience in DataBricks AWS bedrock Microsoft Copilot Studio and Azure ML is plus.

• Prior experience in Pharma commercial is a plus.

• Excellent communication skills and a demonstrated ability to collaborate effectively with cross-functional teams.

• Self-motivated and highly driven individual who can thrive in ambiguous requirements.

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Preferred Skills: