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1 week ago
We are currently seeking a highly skilled Python AI Engineer to join our team.
The ideal candidate will have experience in designing and implementing intelligent frameworks for synthetic and automated test data generation in support of clinical trials, regulatory submissions, and GxP-compliant systems.
Key Responsibilities- Data Generation: Design and implement Python frameworks to generate synthetic clinical and operational datasets, including CDISC-compliant datasets (SDTM, ADaM) for data transformation, analysis, and reporting workflows.
- Simulation: Simulate domain-specific datasets (adverse events, labs, demographics, drug exposure) with variability and referential integrity using generative AI (LLMs, GANs, diffusion models).
- Automation: Develop connectors for Define-XML, Pinnacle21 validation, and statistical programming workflows, as well as use AI-driven automation to simulate rare or complex cases for stress and edge-case testing.
- Validation and Compliance: Ensure adherence to GxP, 21 CFR Part 11, HIPAA, and GDPR standards, and implement anonymization/obfuscation while maintaining clinical and statistical fidelity.
- Documentation and Delivery: Produce validation protocols and documentation for audit and inspection readiness, and embed test data generation into CI/CD pipelines, trial simulations, and automated validation environments.
- Technical Skills: Proficiency in Python, experience with AI and machine learning technologies, and familiarity with clinical data management systems.
- Soft Skills: Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams, including Clinical Data Management, Biostatistics, Pharmacovigilance, and Compliance.
This is an exciting opportunity to leverage your technical expertise and passion for innovation to drive business growth and success.
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