Lead Engineer, Evidence Management
Job in
Raritan, Somerset County, New Jersey, 08869, USA
Listed on 2026-09-07
Listing for:
Jobtailor
Full Time
position Listed on 2026-09-07
Job specializations:
-
IT/Tech
AI Business & Operations, Information & Knowledge Management
Job Description & How to Apply Below
- Serve as Lead Engineer for evidence management capabilities covering regulatory and scientific 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 supporting Scientific Affairs processes and evidence workflows
- Lead AI-enabled modernization by identifying evidence management use cases and designing scalable implementation patterns
- Partner with Regulatory Affairs, Scientific Affairs, Quality, R&D, Supply Chain, Cybersecurity, Privacy, Data Governance, and IT delivery teams
- Act as lead technical advisor for Appian application decisions, integrations, data products, engineering practices, and AI-enabled capabilities
- Own the application architecture strategy and engineering roadmap across Regulatory Affairs and Scientific Affairs
- Design scalable, interoperable, and compliant solutions across platforms, applications, data flows, workflows, integrations, content repositories, and analytics
- Translate regulatory and scientific evidence processes into application designs, engineering patterns, data models, and delivery backlogs
- Drive design governance, technical debt remediation, platform modernization, and cross-system interoperability
- Ensure alignment with enterprise standards for cloud, cybersecurity, privacy, lifecycle management, supportability, and technical sustainability
- Lead Appian-based regulatory workflow, evidence case management, process automation, integration, records, reporting, and user experience capabilities
- Define AI-enabled engineering roadmap covering Generative AI, Machine Learning, NLP, semantic search, knowledge graphs, agentic workflows, and intelligent automation
- Guide AI proofs-of-concept, pilots, and scaled implementations with security, usability, and compliance controls
- Establish controls for monitoring, hallucination risk mitigation, source traceability, human-in-the-loop review, prompt/version governance, and model performance evaluation
- Define data architecture principles and engineering standards for APIs, event-driven integration, workflow orchestration, data lineage, data quality, access control, and interoperability
- Ensure compliance with GxP, SOX, privacy, cybersecurity, auditability, data integrity, validation/qualification, and regulated SDLC practices
- Partner with Quality, Security, Privacy, Regulatory Affairs, Scientific Affairs, and Data Governance stakeholders on technology and AI risk assessment
- Bachelor degree in Computer Science, Engineering, Information Systems, Data Science, AI/ML, or a related field
- 10+ years of progressive experience in software engineering, application architecture, solution architecture, platform architecture, low-code platform architecture, data architecture, or enterprise technology delivery
- Mandatory hands-on experience engineering, architecting, and delivering solutions on the Appian platform
- Expertise in Appian solution design, including process modeling, interfaces, records, integrations, data models, rules, reports, role-based security, application lifecycle governance, and environment management
- Experience leading application engineering delivery in Agile or SAFe environments
- Experience architecting or engineering AI-enabled enterprise solutions, including Generative AI and/or Machine Learning use cases
- Hands-on knowledge of Large Language Models, prompt engineering, semantic search, vector databases, Retrieval-Augmented Generation, model orchestration, AI observability, and responsible AI controls
- Experience designing secure, cloud-native, API-enabled, workflow-enabled, and data-centric platforms in complex enterprise environments
- Experience supporting regulated business functions such as Regulatory Affairs, Scientific Affairs, Quality, Clinical, Safety, R&D, or Life Sciences technology
- Working knowledge of GxP, SOX, privacy, cybersecurity, data integrity, regulated SDLC, validation, qualification, or computerized system assurance practices
- Ability to translate business operating models, regulatory processes, and evidence management needs into scalable technical architectures and delivery-ready engineering designs
- Appian certification or equivalent demonstrated enterprise Appian engineering and architecture experience preferred
- Experience with Regulatory Affairs platforms, RIM solutions, submission management, regulatory intelligence, regulatory analytics, content management, knowledge management systems, or evidence management platforms preferred
- Experience supporting Scientific Affairs, Medical Affairs, evidence generation, scientific content workflows, or knowledge search capabilities preferred
- Experience with Microsoft Azure AI services, Azure OpenAI, Copilot extensibility, AI…
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