Director, AI Architecture & Governance

Sarepta Therapeutics•Cambridge, MA

13h•$206,000 - $257,500•Hybrid

About The Position

The Director, AI Architecture & Governance is a senior technical leadership role responsible for defining and governing enterprise-scale AI and Generative AI architectures across the life sciences value chain. This role establishes the standards, platform/tooling strategy, and governance frameworks required to deliver AI outcomes safely and at scale, while enabling AI/ML engineering resources to execute efficiently. The Director partners closely with Enterprise Systems, Computer System Validation (CSV), and Enterprise Data Systems (EDS) to ensure AI solutions align with application architecture, validation expectations, and enterprise data governance. Success requires strong cross-functional collaboration and communication across scientists, engineers, data teams, and executive stakeholders.

Requirements

Bachelor’s degree required; advanced degree in a quantitative or technical field preferred.
BA/BS degree with 12+ years of related experience
MA/MS degree with 10+ years of related experience
8+ years of experience in AI/ML, data platforms, or enterprise architecture roles, including ownership of reference architectures and cross-team standards.
Experience evaluating platforms/tools and driving adoption in complex enterprise environments.
Strong understanding of AI/ML system architecture and integration patterns.
Experience with modern data platforms and cloud architectures.
Knowledge of governance, security, and access control models for enterprise data and AI systems.
Ability to define scalable patterns for model lifecycle management, auditability, and operationalization.
Track record of influencing cross-functional teams without formal authority.
Excellent communication skills—able to bridge scientists, engineers, CSV/quality partners, and executives.
Execution-oriented leadership—able to translate standards into practical implementation patterns.
Ability to foster an inclusive, collaborative environment and build trust with diverse stakeholders.
Candidates must be authorized to work in the U.S.

Nice To Haves

Experience in biotech/pharma and familiarity with R&D and clinical workflows.
Experience working in regulated environments, including collaboration with CSV/quality organizations.
Experience partnering with data governance organizations on data ownership, quality, and access controls.

Responsibilities

Define and maintain the enterprise AI reference architecture (data, model, orchestration, and integration patterns) to support scalable delivery across R&D, clinical, and operations.
Lead build vs. buy vs. partner decisions and define approved tooling and platform patterns for AI/ML and agentic capabilities.
Establish governance and validation standards for AI/ML solutions, including traceability, auditability, and human oversight, in alignment with CSV and applicable regulatory expectations.
Define data access and security models for AI systems and partner with EDS to ensure alignment with data governance standards, data ownership, and data quality controls.
Maintain oversight of the AI use case portfolio to ensure consistent execution against standards and measurable outcomes; business stakeholders set prioritization.
Drive alignment across teams by defining ownership boundaries and ensuring architectural standards translate into implementable patterns and adoption plans.