Senior Director, Quality Technology
Alnylam Pharmaceuticals
August 30, 2026
Remote friendly (Cambridge, MA)
United States
Operations
Responsibilities:
- Define and execute end-to-end Quality technology strategy across R&D and TOQ aligned to QMS processes, lifecycle requirements, and governance.
- Own lifecycle management (selection, implementation, integration, enhancement, retirement) of Quality applications including Veeva Quality Suite, LabWare LIMS, SAP S/4 QM, and related systems; ensure reliability, scalability, and continuous improvement.
- Oversee delivery and ongoing support of QMS-enabled IT systems, retaining end-to-end oversight of vendor-delivered work; establish governance and accountability.
- Partner with Quality and IT Data/AI to define Quality data models/standards and integration patterns; enable data flow and enterprise data platform integration; ensure GxP data governance, lineage, and quality.
- Enable analytics/AI use cases for Quality (QMS performance monitoring, risk identification/predictive quality, system health/capacity/operational risk) and operationalize at scale.
- Ensure IT system compliance, validation, and data integrity for GxP; support CSV/system assurance and audit/inspection readiness; establish scalable system lifecycle management processes.
- Serve as primary IT partner to Quality leadership; translate priorities into technology roadmaps; support standardization and adoption; build a high-performing Quality Technology team.
Required Qualifications:
- BS/MS/PhD in science or engineering.
- 15+ years IT experience supporting Quality in life sciences.
- Strong knowledge of GxP, Quality processes, and regulatory requirements.
- Proven leadership in enterprise system implementations (e.g., Veeva, LabWare, SAP).
- Solid enterprise systems, data, and integration knowledge.
- Demonstrated ability partnering with senior Quality/IT/business leaders; regulated-environment/audit exposure.
Preferred Qualifications:
- Enterprise data platform familiarity (e.g., Snowflake) and integration patterns.
- Experience with Enterprise Data/AI teams (data modeling/analytics).
- Exposure to Quality analytics/reporting/AI; system architecture/integration/technology strategy.
- Data governance/data integrity framework knowledge; end-to-end product lifecycle experience.
Benefits (as stated):
- Medical/dental/vision; life/disability; lifestyle reimbursement; flexible spending/HSAs; 401(k) match.
- Paid time off, wellness days, holidays, two recharge breaks; family resources and leave.
- Define and execute end-to-end Quality technology strategy across R&D and TOQ aligned to QMS processes, lifecycle requirements, and governance.
- Own lifecycle management (selection, implementation, integration, enhancement, retirement) of Quality applications including Veeva Quality Suite, LabWare LIMS, SAP S/4 QM, and related systems; ensure reliability, scalability, and continuous improvement.
- Oversee delivery and ongoing support of QMS-enabled IT systems, retaining end-to-end oversight of vendor-delivered work; establish governance and accountability.
- Partner with Quality and IT Data/AI to define Quality data models/standards and integration patterns; enable data flow and enterprise data platform integration; ensure GxP data governance, lineage, and quality.
- Enable analytics/AI use cases for Quality (QMS performance monitoring, risk identification/predictive quality, system health/capacity/operational risk) and operationalize at scale.
- Ensure IT system compliance, validation, and data integrity for GxP; support CSV/system assurance and audit/inspection readiness; establish scalable system lifecycle management processes.
- Serve as primary IT partner to Quality leadership; translate priorities into technology roadmaps; support standardization and adoption; build a high-performing Quality Technology team.
Required Qualifications:
- BS/MS/PhD in science or engineering.
- 15+ years IT experience supporting Quality in life sciences.
- Strong knowledge of GxP, Quality processes, and regulatory requirements.
- Proven leadership in enterprise system implementations (e.g., Veeva, LabWare, SAP).
- Solid enterprise systems, data, and integration knowledge.
- Demonstrated ability partnering with senior Quality/IT/business leaders; regulated-environment/audit exposure.
Preferred Qualifications:
- Enterprise data platform familiarity (e.g., Snowflake) and integration patterns.
- Experience with Enterprise Data/AI teams (data modeling/analytics).
- Exposure to Quality analytics/reporting/AI; system architecture/integration/technology strategy.
- Data governance/data integrity framework knowledge; end-to-end product lifecycle experience.
Benefits (as stated):
- Medical/dental/vision; life/disability; lifestyle reimbursement; flexible spending/HSAs; 401(k) match.
- Paid time off, wellness days, holidays, two recharge breaks; family resources and leave.