Lead Engineer, Evidence Management

Johnson & Johnson

Confirmed live 2 days ago High trust
Closes in 6 days Hybrid

Quick summary

Work type
Hybrid
Location
Raritan, NJLimerick, Ireland, Ireland
Salary
$102,000–$175,950 / yr
Employment
Full-time
Posted
5 days ago
Freshness
Confirmed live 2 days ago
Closes
Nov 6, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $203k
This role $139k
$85k $262k
below market most similar roles pay here above market

This role pays less than 94% of similar roles. Most pay $167,650–$237,750 — the blue band above. At the midpoint, this role pays about $139k versus about $203k for comparable roles.

Based on 240 similar postings.

Employer

About Johnson & Johnson

Johnson & Johnson is a multinational corporation operating in three main segments: consumer health products, pharmaceuticals, and medical devices, known for brands like Tylenol, Band-Aid, and Janssen. Industry: Pharmaceuticals & Medical Devices

Johnson & Johnson currently has 49 open roles on FindRole.

Listed pay typically runs $119,500–$206,137 across 38 roles with salary data.

Most-posted roles

View all roles at Johnson & Johnson

At a glance

TL;DR · Lead Engineer, Evidence Management

The Lead Engineer, Evidence Management joins the Scientific Affairs and Regulatory Affairs team to provide engineering leadership, application architecture, and delivery governance for the evidence management digital ecosystem. This role focuses on designing and maintaining scalable, compliant solutions for regulatory planning, submissions, and scientific evidence collaboration. The successful candidate will lead Appian-first engineering, utilizing Appian solution design, integrations, and SAFe delivery practices to automate workflows and manage data flows. Key responsibilities include defining AI-enabled roadmaps involving Generative AI, Machine Learning, and NLP while ensuring GxP and SOX compliance. You will translate complex business needs into technical architectures, managing evidence intake, assessment, and regulatory intelligence. Required expertise includes hands-on Appian platform experience, cloud-native API design, and knowledge of regulated SDLC practices within the life sciences domain.

What you'll do

  • Own and maintain the application architecture strategy and engineering roadmap for evidence management capabilities.
  • Design scalable, interoperable, and compliant solutions for regulatory platforms, data flows, and workflows.
  • Translate complex regulatory and scientific evidence processes into practical application designs and data models.
  • Lead engineering for Appian-based regulatory workflows, including process automation, integrations, and user experience.
  • Define the AI-enabled engineering roadmap for Generative AI, Machine Learning, and intelligent automation.
  • Establish engineering standards for APIs, event-driven integration, data lineage, and platform interoperability.
  • Ensure all architecture decisions support GxP, SOX, privacy, and cybersecurity compliance requirements.
  • Partner with cross-functional stakeholders to translate business needs into maintainable technology solutions.

What we're looking for

  • Bachelor degree in Computer Science, Engineering, Information Systems, Data Science, AI/ML, or a related field.
  • 10+ years of progressive experience in software, application, platform, or enterprise technology architecture and delivery.
  • Mandatory hands-on experience engineering, architecting, and delivering solutions on the Appian platform.
  • Demonstrated expertise in Appian solution design, including process modeling, integrations, data models, and application lifecycle governance.
  • Strong experience leading application engineering delivery in Agile or SAFe environments.
  • Demonstrated experience architecting or engineering AI-enabled enterprise solutions, including Generative AI and Machine Learning.
  • Hands-on knowledge of Large Language Models, prompt engineering, vector databases, and responsible AI controls.
  • Working knowledge of GxP, SOX, privacy, cybersecurity, data integrity, and regulated SDLC practices.

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