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Insmed

Develops therapies for rare diseases

Director of Digital Systems Quality Assurance: AI/ML Systems

Regulatory & Quality (Life Sciences)Updated on Nov 13
Full-timeBridgewater, NJ, USA

About the Job

Requirements

  • A bachelor's degree in Life Sciences, Computer Science, Data Science, Engineering, Pharmacy, or a related scientific or technical discipline is required.
  • A minimum of 10 years of relevant Quality Assurance experience is required.
  • Demonstrated experience building, leading, or significantly contributing to AI/ML quality or validation frameworks in an FDA-, EMA-, or equivalently regulated environment.
  • Working knowledge of MLOps, AIOps, and related concepts and tools, including model versioning, CI/CD, experiment tracking, and drift monitoring platforms.
  • Familiarity with cloud-based AI/ML platforms such as Vertex and Bedrock, and data warehouses such as Snowflake.
  • Hands-on experience with GxP computer system validation (CSV) and/or Computer Software Assurance (CSA) across multiple domains, including clinical, manufacturing, laboratory, or commercial.
  • Experience reviewing multiple GMP records and processes, including CSV validation protocols, deviations, CAPA, and SOPs.
  • Strong communication skills, both verbal and written.
  • Ability to manage projects and variable workloads.
  • Organization and attention to detail, clarity, accuracy, and conciseness.
  • Ability to exhibit the company's core values of Passion, Accountability, Collaboration, Integrity, and Respect, and position-specific competencies.

Responsibilities

  • Represent Quality Assurance in designing, governing, and continuously improving a regulatory-compliant framework for AI/ML solutions across the global GxP-regulated digital landscape.
  • Lead assessment, classification, risk evaluation, validation, and implementation design of AI/ML-enabled systems, aligning them with global regulatory expectations and quality standards.
  • Partner with IT System Owners, Business Owners, and CSV leads to drive a unified, risk-based AI/ML quality oversight approach across functional domains and sites.
  • Serve as the enterprise QA lead for regulated AI/ML solutions, provide independent QA review of Computer Software Validation lifecycle documents, and facilitate site IT Change Control processes.
  • Partner with business stakeholders to understand AI/ML use-case needs and translate them into compliant, risk-proportionate QA solutions.
  • Support AI/ML-specific risk assessment methodologies aligned with GAMP 5, FDA AI/ML guidance, the 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 development and maintenance of AI/ML validation lifecycle documentation, including AI/ML Risk Assessments, Validation Plans, Model Cards, Performance Qualification (PQ) protocols, and Ongoing Performance Monitoring (OPM) plans.
  • Embed responsible AI principles in solution design and governance, including bias assessment, human oversight requirements, and transparency standards aligned with EU AI Act risk classifications.
  • Ensure AI/ML models and systems used 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 and agentic AI use cases in GxP-adjacent environments, including hallucination risk, non-determinism, prompt governance, and output auditability standards.
  • Define ongoing model monitoring, drift detection, retraining governance, and change control requirements for AI/ML solutions in validated states.
  • Write SOPs and other quality system documentation, and assist other departments with generating, reviewing, approving, and maintaining such documents.
  • Provide guidance, training, and mentoring to team members on AI/ML concepts, regulatory expectations, validation approaches, and risk-based QA methodology; develop AI training requirements as necessary.
  • Lead or participate in AI/ML vendor assessments, audits, and qualification activities to ensure third-party solutions meet quality and regulatory standards.
  • Support regulatory inspections and internal and external audits as the AI/ML QA subject matter expert, prepare inspection-readiness materials, and respond to agency questions on AI/ML topics.
  • Travel domestically approximately 30% of the time.

Desired Qualifications

  • An advanced degree (MS, MBA, or PhD) in a relevant discipline; candidates with an advanced degree and a minimum of 8 years of relevant experience will be considered.
  • Preferred experience in Data Integrity, 21 CFR Part 11, Annex 11, GAMP 5, SDLC (Agile or Waterfall), and CSA.

About the Company

Insmed

Develops therapies for rare diseases

Insmed focuses on developing and delivering therapies for serious and rare diseases. Its products come from a pipeline of clinical trials and approved treatments, sold to patients in global markets with offices in Bridgewater, NJ, Europe, and Japan. The company’s work combines research and development, regulatory approvals, and commercialization to bring therapies from discovery to patients. Insmed differentiates itself by addressing unmet medical needs in rare diseases and maintaining a global infrastructure that supports development, approval, and patient access. The goal is to improve patient outcomes by providing effective treatments for conditions with limited existing options.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Bridgewater Township, New Jersey
Founded
1988

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