
AI Engineer
4 days ago
Job Title:
AI Engineer - Synthetic Data Generation
About the Job:
We are seeking an experienced AI engineer to design and implement intelligent frameworks for generating synthetic test data in support of clinical trials, regulatory submissions, and GxP-compliant systems.
This role will leverage AI/ML and Python automation to deliver high-quality, audit-ready datasets that reduce reliance on production data, accelerate testing cycles, and ensure compliance with FDA, EMA, and global regulatory standards.
Key Responsibilities:- Synthetic Test Data Automation:
- Develop Python frameworks to generate synthetic clinical and operational datasets.
- Produce CDISC-compliant datasets (SDTM, ADaM) for data transformation, analysis, and reporting workflows.
- Simulate domain-specific datasets (adverse events, labs, demographics, drug exposure) with variability and referential integrity.
- Develop connectors for Define-XML, Pinnacle21 validation, and statistical programming workflows.
- AI/ML in Data Generation:
- Apply generative AI (LLMs, GANs, diffusion models) to model realistic clinical scenarios.
- Create synthetic patient journeys across EDC, eCOA, CTMS, LIMS, and PV systems.
- Use AI-driven automation to simulate rare or complex cases for stress and edge-case testing.
- Compliance & Data Governance:
- Ensure adherence to GxP, 21 CFR Part 11, HIPAA, and GDPR standards.
- Implement anonymization/obfuscation while maintaining clinical and statistical fidelity.
- Produce validation protocols and documentation for audit and inspection readiness.
- Collaboration & Integration:
- Work with Clinical Data Management, Biostatistics, Pharmacovigilance, and Compliance teams to gather requirements.
- Embed test data generation into CI/CD pipelines, trial simulations, and automated validation environments.
- Partner with SMEs to validate AI-generated datasets for regulatory acceptability.
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