Director, Quality Assurance AI/ML Systems

Location: NJ Corporate Headquarters

At Insmed, every moment and every patient counts — and so does every person who joins in. As a global biopharmaceutical company dedicated to transforming the lives of patients with serious and rare diseases, you’ll be part of a community that prioritizes the human experience, celebrates curiosity, and values every person’s contributions to meaningful progress. That commitment has earned us recognition as Science magazine’s No. 1 Top Employer for five consecutive years, certification as a Great Place to Work® in the U.S., and a place on The Sunday Times Best Places to Work list in the UK.

For patients, for each other, and for the future of science, we’re in. Are you?

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.