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Sr. Director, Lab-to-Product Platform & Operations Technology

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Magnolia Recruiting
Full Time position
Listed on 2026-04-20
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Overview

Alnylam is seeking a strategic and pragmatic technology leader to serve as Senior Director, Lab‑to‑Product Platform & Operations Technology. This on‑site role is based in Cambridge, MA, with regular engagement at the Cambridge labs and Norton/Alewife manufacturing sites, and directs relationships with external execution partners.

The role owns the core digital platforms, services, lab computing environment, and operational technologies that power laboratory operations across Research, CMC, and Quality Control, as well as digital enablement of plant‑floor (shopfloor) operational technologies.

Beyond internal operations, the position oversees operational technology enablement, secure data exchange, workflow interoperability, and validated system readiness that support external execution partners—including CROs, external research labs, development collaborators, contract testing labs, and external manufacturing partners.

Key Responsibilities 1. Own and operate core lab, plant, and external partner operational platforms
  • Lead digital capabilities that support lab operations across Research, CMC, and QC, including LIMS, ELN/LES, sample & inventory management, registration, lab automation enablement, instrument integration, lab computing, lab system validation, and operational data capture.
  • Oversee plant‑floor operational technologies such as equipment/instrument connectivity, environmental and facility monitoring interfaces, materials tracking, barcode/RFID data capture, and automated data collection (excluding MES and supply chain systems).
  • Enable operational technology connectivity, workflow interoperability, and validated data exchange with CROs, external research labs, development partners, contract testing labs, and external manufacturers.
  • Support validated data handoffs, sample/material traceability, workflow tracking, and operational interfaces across hybrid (internal + external) execution models.
  • Ensure reliability, compliance, validated state, lifecycle management, and service continuity across internal systems and partner‑connected operational interfaces.
  • Oversee lab/operational system validation activities in partnership with Quality to maintain GxP compliance and data integrity across all execution environments.
2. Build the Lab‑to‑Product Platform (Internal + External Execution Model)
  • Architect and deliver the operational platform that connects experiment execution, sample workflows, QC testing, plant operational activities, and external execution and release workflows.
  • Provide reusable platform components including metadata standards, workflow modules, instrument connectors, validated integration frameworks, and operational data pipelines that external partners can adopt or interface with.
  • Ensure seamless interoperability with scientific platforms owned by ReDev Technology, manufacturing/enterprise systems owned by Manufacturing/CMC/Supply Chain Technology, and external research, development, QC, and manufacturing partner systems.
  • Establish secure, scalable, validated patterns for partner connectivity (e.g., APIs, secure file exchange, partner portals, event/data streams).
3. Lead a high‑performing operations‑focused technology team
  • Build and develop talent and capabilities across product management, engineering/architecture, lab computing support, instrument connectivity, and operational platform engineering.
  • Define support, governance, onboarding, and escalation models for external partners, including SLAs and service continuity plans in collaboration with ReDev and TOQ.
  • Drive a culture centered on operational excellence, validation rigor, compliance, accountability, and pragmatic problem‑solving.
  • Establish standards, governance, and best practices for lab/plant operational technology, including lab system validation frameworks.
4. Deliver robust operational data integration
  • Work closely with the Data & AI organization to ensure operational data—including external partner‑generated data—is structured, contextualized, and AI‑ready.
  • Implement consistent metadata, data capture, and validated interface practices across internal and external operations.
  • Enable cross‑system visibility into…
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