Director, Quality Assurance AI/ML Systems

About the Role

The Director of Digital Systems Quality Assurance (DSQA)- AI/ML is an enterprise-level role responsible for representing QA in the design, governance, and continuous improvement of a regulatory-compliant framework for Artificial Intelligence (AI) and Machine Learning (ML) solutions across Insmed's global GxP-regulated digital landscape. This position serves as the lead for the assessment, classification, risk evaluation, validation, and implementation design of AI/ML-enabled systems, ensuring alignment with global regulatory expectations and Insmed's quality standards. Working in close partnership with IT System Owners, Business Owners, and CSV leads, this role drives a unified, risk-based approach to AI/ML quality oversight spanning all DSQA functional domains and Insmed sites. The position serves as the enterprise QA lead for regulated AI/ML solutions, providing independent QA review of Computer Software Validation lifecycle documents and facilitating site IT Change Control processes across all functional areas.

What You'll Do

In this role, you will partner with business stakeholders across Insmed to understand AI/ML use-case needs and translate them into compliant, risk-proportionate QA solutions. You will also have responsibility for:

• Support AI/ML-specific risk assessment methodologies aligned with GAMP 5, FDA AI/ML guidance, EU AI Act, Annex 11, and 21 CFR Part 11.
• Represent Digital QA in cross-functional governance forums, steering committees, and working groups focused on AI/ML adoption and compliance.
• Support the Development and maintenance of AI/ML-specific validation lifecycle documentation including AI/ML Risk Assessments, Validation Plans, Model Cards, Performance Qualification (PQ) protocols, and Ongoing Performance Monitoring (OPM) plans.
• Ensure responsible AI principles are embedded in the design and governance of AI/ML solutions, including bias assessment, human oversight requirements, and transparency standards aligned with EU AI Act risk classifications.
• Ensure AI/ML models and systems deployed in GxP contexts maintain data integrity, auditability, explainability, and traceability in alignment with global regulatory expectations.
• Provide QA oversight and governance guidance for Generative AI (GenAI) and agentic AI use cases in GxP-adjacent environments, including hallucination risk, non-determinism, prompt governance, and output auditability standards.
• Define requirements for ongoing model monitoring, drift detection, retraining governance, and change control processes for AI/ML solutions in validated states.
• Writes SOPs and other quality system documentation, assists other departments with the generation, review and approval and maintenance of such documents.
• Provide guidance, training, and mentoring to the Insmed team members on AI/ML concepts, regulatory expectations, validation approaches, and risk-based QA methodology.
• Development of AI Training requirements (as necessary).
• Lead or participate in AI/ML-related vendor assessments, audits, and qualification activities to ensure third-party AI/ML solutions meet Insmed's quality and regulatory standards.
• Support regulatory inspections and internal/external audits as the AI/ML QA SME; prepare inspection-readiness materials and respond to agency questions on AI/ML topics.

Who You Are

You have a Bachelor's degree (BS) in Life Sciences, Computer Science, Data Science, Engineering, Pharmacy, or a related scientific or technical discipline required. Advanced degree (MS, MBA, or PhD) in a relevant discipline preferred; candidates with an advanced degree and a minimum of 8 years of relevant experience will be considered.

Additionally you have:

• A minimum of 10 years of relevant Quality Assurance experience required; at least 3–5 years in a Director-level or senior leadership capacity.
• Demonstrated experience building, leading, or significantly contributing to AI/ML quality or validation frameworks in a regulated (FDA, EMA, or equivalent) environment.
• Working knowledge of MLOps, AIOps and similar concepts and associated tools and concepts (e.g., model versioning, CI/CD, experiment tracking, drift monitoring platforms); familiarity with cloud-based AI/ML platforms (Vertex, Bedrock) and Data warehouse such as Snowflake preferred.
• Hands-on experience with GxP computer system validation (CSV) and/or Computer Software Assurance (CSA) across multiple domains (clinical, manufacturing, laboratory, commercial).
• Experience as QA reviewer of several GMP records and processes: CSV Validation Protocols, Deviations, CAPA, SOPs, etc.
• Preferred experience in Data Integrity, 21 CFR Part 11, Annex 11, GAMP 5, SDLC (Agile or Waterfall), CSA.
• Must have excellent communication skills (verbal and written).
• Demonstrate ability to manage projects and variable workloads.
• Highly organized with a strong attention to details, clarity, accuracy, and conciseness.
• Must successfully exhibit Insmed's five (5) core corporate values: Passion, Accountability, Collaboration, Integrity and Respect; along with any other position specific competencies.

Travel Requirements

This role requires occasional domestic travel approximately 30%.

Where You'll Work

This is a hybrid role based out of our Bridgewater, NJ Headquarters. You'll work remotely most of the time, with in-person collaboration when it matters most.