Director, AI Architecture & Governance
Sarepta Therapeutics
August 18, 2026
Remote friendly (Cambridge, MA)
United States
IT
Responsibilities:
- Define and govern enterprise-scale AI and Generative AI architectures across the life sciences value chain.
- Establish standards, platform/tooling strategy, and governance frameworks to deliver AI outcomes safely and at scale.
- Partner with Enterprise Systems, Computer System Validation (CSV), and Enterprise Data Systems (EDS) to align AI solutions with application architecture, validation expectations, and enterprise data governance.
- Define and maintain enterprise AI reference architecture (data, model, orchestration, integration patterns) for 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 (traceability, auditability, human oversight) aligned with CSV and regulatory expectations.
- Define data access and security models for AI systems; align with data governance, data ownership, and data quality controls.
- Provide portfolio execution oversight to ensure consistent execution against standards and measurable outcomes (prioritization set by business stakeholders).
- Drive cross-functional adoption by translating architectural standards into implementable patterns and adoption plans.
Qualifications:
- Bachelor’s degree required; advanced degree in quantitative/technical field preferred.
- 12+ years (BA/BS) or 10+ years (MA/MS) related experience.
- 8+ years 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.
Skills:
- AI/ML system architecture and integration patterns.
- Modern data platforms and cloud architectures.
- Governance, security, and access control models for enterprise data and AI systems.
- Scalable patterns for model lifecycle management, auditability, and operationalization.
- Influence without formal authority; strong cross-functional communication.
Preferred:
- Biotech/pharma experience with R&D and clinical workflows.
- Experience in regulated environments with CSV/quality collaboration.
- Partnering with data governance on ownership, quality, and access controls.
Application instructions:
- Apply if you are solution-oriented, comfortable with ambiguity/candor, and prioritize kindness and integrity.
Work arrangement:
- Hybrid; on-site at a U.S. facility and/or occasional in-person company events.
Benefits/compensation:
- Targeted salary range: $206,000 - $257,500 per year.
Eligibility:
- Must be authorized to work in the U.S.
- Define and govern enterprise-scale AI and Generative AI architectures across the life sciences value chain.
- Establish standards, platform/tooling strategy, and governance frameworks to deliver AI outcomes safely and at scale.
- Partner with Enterprise Systems, Computer System Validation (CSV), and Enterprise Data Systems (EDS) to align AI solutions with application architecture, validation expectations, and enterprise data governance.
- Define and maintain enterprise AI reference architecture (data, model, orchestration, integration patterns) for 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 (traceability, auditability, human oversight) aligned with CSV and regulatory expectations.
- Define data access and security models for AI systems; align with data governance, data ownership, and data quality controls.
- Provide portfolio execution oversight to ensure consistent execution against standards and measurable outcomes (prioritization set by business stakeholders).
- Drive cross-functional adoption by translating architectural standards into implementable patterns and adoption plans.
Qualifications:
- Bachelor’s degree required; advanced degree in quantitative/technical field preferred.
- 12+ years (BA/BS) or 10+ years (MA/MS) related experience.
- 8+ years 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.
Skills:
- AI/ML system architecture and integration patterns.
- Modern data platforms and cloud architectures.
- Governance, security, and access control models for enterprise data and AI systems.
- Scalable patterns for model lifecycle management, auditability, and operationalization.
- Influence without formal authority; strong cross-functional communication.
Preferred:
- Biotech/pharma experience with R&D and clinical workflows.
- Experience in regulated environments with CSV/quality collaboration.
- Partnering with data governance on ownership, quality, and access controls.
Application instructions:
- Apply if you are solution-oriented, comfortable with ambiguity/candor, and prioritize kindness and integrity.
Work arrangement:
- Hybrid; on-site at a U.S. facility and/or occasional in-person company events.
Benefits/compensation:
- Targeted salary range: $206,000 - $257,500 per year.
Eligibility:
- Must be authorized to work in the U.S.