Lead Engineer, Evidence Management

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.

Job Function:

Technology Product & Platform Management

Job Sub Function:

Agile

Job Category:

Scientific/Technology

All Job Posting Locations:

Limerick, Ireland, Raritan, New Jersey, United States of America

Job Description:

We are searching for the best talent for a Lead Engineer, Evidence Management candidate to be located in either Raritan, NJ, or Limerick, Ireland.

Please note that this role is available across multiple countries and may be posted under different requisition numbers to comply with local requirements. While you are welcome to apply to any or all of the postings, we recommend focusing on the specific country(s) that align with your preferred location(s):

Raritan, NJ, and Limerick, Ireland.

Limerick, Ireland - Requisition Number: R-097658

Remember, whether you apply to one or all of these requisition numbers, your applications will be considered as a single submission.

Lead Engineer, Evidence Management Digital Ecosystem

Scientific Affairs and Regulatory Affairs | Appian-first engineering and application architecture leadership

Lead Engineer, Evidence Management Digital Ecosystem

Scientific Affairs and Regulatory Affairs | Appian-first engineering and application architecture leadership

About Johnson & Johnson, MedTech

Fueled by innovation at the intersection of biology and technology, we are developing the next generation of smarter, less invasive, more personalized treatments. Your unique talents will help patients on their journey to wellness. Learn more at https://www.jnj.com/medtech

This is primarily a hybrid role for candidates currently based within commuting distance of a Johnson & Johnson office in the United States (preferably New Jersey). Remote candidates may also be considered on a limited basis if they hold strong credentials and required experience.

Position Summary

The Lead Engineer, Evidence Management is responsible for engineering leadership, application architecture, and delivery governance for the Evidence Management digital ecosystem spanning Scientific Affairs and Regulatory Affairs.

This is primarily an Appian-first, AI-enabled, and ecosystem-oriented engineering role. The successful candidate must bring strong hands-on and strategic experience with Appian platform architecture, Appian solution design, Appian integrations, application architecture, engineering quality practices, and SAFe delivery. Most work expectations remain primarily focused on the Regulatory Affairs domain, with Scientific Affairs included as an adjacent and expanding evidence management stakeholder group.

Mandatory Capability Requirement : Candidates will be evaluated for demonstrated ability to engineer, architect, and deliver secure, compliant, scalable solutions that create measurable business value for Regulatory Affairs and support evidence management needs across Scientific Affairs. Appian technology skills are mandatory for this position.

Role Purpose

• •Serve as the Lead Engineer for evidence management capabilities covering regulatory and scientifc workflow, case management, process automation, content/data flows, integrations, and user experience.
• •Define and guide application architecture for platforms supporting regulatory planning, submissions, evidence intake, evidence assessment, regulatory intelligence, workflow automation, post-approval activities, scientific evidence collaboration, and analytics.
• •Maintain primary focus on Regulatory Affairs delivery priorities while designing solutions that can also support Scientific Affairs processes, evidence workflows, and cross-functional collaboration.
• •Lead AI-enabled modernization by identifying high-value evidence management use cases, designing scalable implementation patterns, and ensuring responsible adoption in regulated environments.
• •Partner with Regulatory Affairs, Scientific Affairs, Quality, R&D, Supply Chain, Cybersecurity, Privacy, Data Governance, and IT delivery teams to translate complex business needs into compliant, maintainable technology solutions.
• •Act as the lead technical advisor for Appian application decisions, integrations, data products, engineering practices, and AI-enabled capabilities across the evidence management ecosystem.

Key Responsibilities

1. Evidence Management Application Engineering and Architecture

· Own and maintain the application architecture strategy and engineering roadmap for evidence management capabilities across Regulatory Affairs and Scientific Affairs.

· Design scalable, interoperable, and compliant solutions across regulatory platforms, Appian applications, data flows, workflows, integrations, content repositories, and analytics capabilities.

· Translate complex regulatory and scientific evidence processes into practical application designs, engineering patterns, data models, and delivery backlogs.

· Drive design governance for new capabilities, major enhancements, technical debt remediation, platform modernization, and cross-system interoperability.

· Ensure solution designs align with enterprise standards for cloud, cybersecurity, privacy, lifecycle management, supportability, and technical sustainability.

· Lead engineering and application architecture for Appian-based regulatory workflow, evidence case management, process automation, integration, records, reporting, and user experience capabilities and define Appian design standards

2. Evidence Management Leadership

· Maintain deep understanding of Regulatory Affairs operating processes and technology needs across planning, submissions, regulatory intelligence, workflow orchestration, post-approval activities, content management, compliance, and analytics.

· Ensure evidence management capabilities support traceability, auditability, role-based access, status visibility, decision history, and inspection-ready records where required.

· Extend the evidence management architecture and engineering patterns to support Scientific Affairs use cases such as evidence intake, evidence evaluation, collaboration workflows, knowledge search, scientific content traceability, and analytics.

· Identify common process, data, content, workflow, and integration patterns that can be reused across Scientific Affairs and Regulatory Affairs while respecting domain-specific controls.

3. Data Management and AI-enabled Evidence Management

· Define the AI-enabled engineering roadmap for evidence management, including Generative AI, Machine Learning, NLP, semantic search, knowledge graphs, agentic workflows, and intelligent automation where appropriate.

· Guide proof-of-concepts, pilots, and scaled implementations for AI capabilities with clear business value, security, usability, and compliance controls.

· Establish patterns for monitoring, hallucination risk mitigation, source traceability, human-in-the-loop review, prompt/version governance, and model performance evaluation.

· Define data architecture principles for evidence metadata, Appian data models, regulatory master data, scientific evidence content, operational data, unstructured content, and analytics-ready data products.

· Establish engineering standards for APIs, event-driven integ