Director, Cyber Architecture & Engineering

Spyglass Partners, LLC; Boston (MA); Hybrid; USD 216,000 - 292,000; Full time

Job summary

Alnylam is seeking a Director of Enterprise Architecture in a hybrid Cambridge, MA role. You will define reference architectures, technical standards, and governance to enable data, AI, and integration solutions within a regulated life sciences environment.

You will lead one to two architects, influence a larger matrixed tech org, and work with cross‑functional teams to ensure coherent, compliant enterprise direction.

Qualifications

• 10+ years in architecture or leadership roles in biotech or regulated env.

Responsibilities

• Define enterprise reference architectures and standards for data, AI, integration, and governance.
• Own Gate 0 architecture review process and ADRs for reusable patterns.
• Prototype and pressure-test architecture decisions with engineering teams.

Skills

Architecture leadership

Enterprise-scale systems

Regulated domain knowledge

Hands-on coding & patterns

Job description

Alnylam is the world's leading RNAi therapeutics company. Our 2030 ambition depends on world-class data, engineering, and AI capabilities that help accelerate science, strengthen operations, and scale innovation across the enterprise. The Director, Enterprise Architecture will define the reference architectures, technical standards, and governance patterns that enable data, AI, and integration solutions to be built consistently across a regulated life sciences environment. This role reports to the Head of Data, AI & Engineering and is expected to directly lead one to two architects while influencing a broader matrixed technology organization spanning ReDev, Development, Manufacturing & Supply, Commercial, and G&A. This is a hybrid role based in Cambridge, MA, with two days per week onsite.

Responsibilities

• Define enterprise reference architectures and technical standards for data, AI, integration, semantic layers, data products, and the platform capabilities required to support governed AI adoption.
• Own the Gate 0 architecture review process, including vendor AI assessments, architecture decision records, reusable pattern libraries, and standards that reduce duplication across teams.
• Prototype and pressure-test architecture decisions in partnership with engineering teams, translating working builds into reusable patterns before they are adopted as enterprise direction.
• Design the technical enforcement layer for enterprise data governance, including lineage, catalog and glossary integration, classification, data quality controls, stewardship workflows, policy-driven access, and master/reference data patterns.
• Establish scalable architecture patterns across clinical, regulatory, safety, quality, manufacturing, commercial, and G&A domains so regulated data can be governed consistently without bespoke solutions for each area.
• Define integration, retrieval, authorization, identity propagation, and audit patterns for AI-enabled systems, including agent and tool use and governed model access to enterprise data.
• Partner with AI, analytics, platform engineering, network, security, and business technology leaders to ensure architecture decisions are coherent, secure, practical, and aligned to regulated life sciences requirements.

Qualifications Required

• 10 or more years of experience in architecture, engineering, or related technology leadership roles, including a meaningful portion in biotech, pharmaceutical, life sciences, or another highly regulated environment.
• Demonstrated ability to architect and ship production systems at enterprise scale, with continued hands‑on fluency in code, platform patterns, and technical design tradeoffs.
• Working knowledge of GxP validated systems and the practical application of 21 CFR Part 11, EU Annex 11, and GAMP 5 to data platforms, integration patterns, and AI-enabled systems.
• Experience with regulated data domains such as clinical, regulatory, safety and pharmacovigilance, quality, manufacturing and supply, commercial, HCP, HCO, or patient‑level data.
• Knowledge of privacy, transparency, data governance, and AI governance expectations, including lineage, cataloging, classification, stewardship, data quality controls, model risk classification, and third‑party AI assessment.

U.S. Pay Range $215,900.00 - $292,100.00