Artificial Intelligence Software Developer

1 week ago


Lucknow, Uttar Pradesh, India beBeeDataEngineer Full time ₹ 50,00,000 - ₹ 80,00,000

We are seeking a Python AI Engineer to design and implement intelligent frameworks for synthetic test data generation.

Key Responsibilities
  • To build Python frameworks that generate synthetic clinical and operational datasets, ensuring they adhere to CDISC standards (SDTM, ADaM).
  • Produce datasets compliant with these standards, suitable for data transformation, analysis, and reporting workflows.
  • Simulate domain-specific datasets with variability and referential integrity, focusing on adverse events, labs, demographics, and drug exposure.
  • Develop connectors for Define-XML, Pinnacle21 validation, and statistical programming workflows.
Ai/ml in Data Generation
  • Apply generative Ai techniques, such as llms, gans, diffusion models, to model realistic clinical scenarios.
  • Create synthetic patient journeys across edc, ecoa, ctms, lims, and pv systems, utilizing Ai-driven automation.
  • Simulate rare or complex cases for stress and edge-case testing, ensuring regulatory compliance.
Compliance & Data Governance
  • Ensure adherence to GxP, 21 CFR Part 11, HIPAA, and GDPR standards, maintaining clinical and statistical fidelity.
  • Implement anonymization/obfuscation methods while preserving the accuracy of generated data.
  • Produce validation protocols and documentation for audit and inspection readiness.
Required Skills & Qualifications
  • Strong expertise in Python, including libraries like pandas, numpy, scikit-learn, pytorch/tensorflow, and langchain.
  • Familiarity with CDISC standards and clinical data management systems, including Medidata Rave and Veeva CDB.
  • Knowledge of GxP/21 CFR Part 11 and regulated data handling practices.
  • Experience with test automation frameworks and validation tools, such as Pinnacle21.

Candidate Profile

  • Background in supporting clinical trial systems.
  • Understanding of statistical workflows and integration into test pipelines.
  • Cloud experience for secure Ai/ml deployment.
  • Experience with inspection readiness and validation documentation in pharma.


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