Tech Professional, Quality Systems, AI

Key Responsibilities

• Provides day-to-day technical support for enterprise quality systems, responding to and diagnosing issues through discussion with users, including troubleshooting, fault rectification, and problem escalation.
• Supports and enhances validated quality platforms covering complaint handling, CAPA, nonconformance, deviations, change control, document management, training records, and audit management.
• Identifies, evaluates, and delivers AI and automation use cases across quality processes — including complaint triage and classification, adverse event signal detection, document summarization, and intelligent search across quality records.
• Partners with Data Science and AI teams to define data requirements, validate model outputs, and operationalize AI-enabled capabilities within quality workflows.
• Ensures AI and automation solutions applied to quality systems meet GxP, 21 CFR Part 11, and data integrity (ALCOA+) expectations, including documented validation and human-in-the-loop controls.
• Analyzes quality system data to identify trends, recurring issues, and process bottlenecks, and translates findings into system and process improvement recommendations.
• Supports computer system validation activities including requirements documentation, test script execution, traceability, and change control for quality platform changes.
• Builds and maintains reporting, dashboards, and metrics that provide Quality leadership with visibility into system performance, record aging, and compliance posture.
• Partners with Quality process owners to gather requirements, configure system enhancements, and support user acceptance testing and release activities.
• Assesses the quality systems implications of technology change — including platform migrations, ERP/PLM integrations, and separation/carve-out activity — and defines requirements ahead of cutover.

Qualifications

Education Required: Bachelor's degree in Computer Science, Information Systems, Engineering, Life Sciences, Quality, or a related discipline. Preferred: Master's degree in Information Systems, Data Science, or Engineering.

Experience and Skills Required: 6 years of progressive experience supporting enterprise quality systems, regulated business applications, or quality technology in a manufacturing or MedTech environment. Hands-on experience with enterprise quality management systems (e.g., Veeva Vault QMS, TrackWise, ETQ, Sparta, or equivalent) covering complaint, CAPA, nonconformance, and document control processes. Working knowledge of GxP, 21 CFR Part 11, computer system validation, and data integrity (ALCOA+) requirements. Demonstrated experience identifying and delivering automation or AI-enabled improvements within business or quality processes. Strong SQL and data analysis skills, with the ability to profile and interpret quality data across systems. Experience supporting validated system changes through formal change control, testing, and documentation. Strong troubleshooting and root cause analysis skills for application, integration, and data issues. Effective communication skills, with the ability to work across Quality, Regulatory, Manufacturing, and Technology stakeholders.

Preferred: MedTech or medical device experience; familiarity with ISO 13485, EU MDR, and FDA QSR/QMSR requirements. Hands-on experience applying Generative AI / LLM-enabled tooling to complaint triage, document review, knowledge retrieval, or quality record summarization. Familiarity with machine learning concepts, model evaluation, and responsible AI controls in a regulated context. Experience integrating quality systems with ERP (SAP), PLM, and manufacturing execution systems. Proficiency with Python or a comparable scripting language for automation and data workflows. Experience with reporting and visualization tools (Power BI, Tableau) for quality metrics and executive dashboards. Experience supporting quality systems migration or stand-up within a divestiture, carve-out, or standalone entity. Exposure to intelligent automation platforms (RPA, workflow automation) applied to quality operations.

Other: Travel up to 20% domestic travel expected across DePuy Synthes manufacturing and office sites. Language: English proficiency required. Certifications: Lean/Six Sigma, ASQ CQE/CQA, ITIL v4 Foundation, or relevant quality systems platform certification preferred. AI/ML or cloud certifications (Azure AI Engineer, AWS Machine Learning) a plus.