Python AI Engineer

7 days ago

India Darsan Technologies, Inc Full time

Overview

Compensation range: 15-25 LPA

We are seeking a 5+ year experienced Python AI Engineer with expertise in synthetic and automated test data generation to support clinical trials, regulatory submissions, and GxP-compliant systems across the life sciences domain.

This role focuses on building intelligent frameworks that generate high-quality, audit-ready datasets for use in clinical data management (CDM), biostatistics, pharmacovigilance, and regulatory validation environments. By leveraging AI/ML techniques and Python-based automation, you will help reduce dependency on production data, accelerate testing cycles, and ensure compliance with FDA, EMA, ICH E6, and 21 CFR Part 11 requirements.

Key Responsibilities

Synthetic Test Data Automation

- Design and implement Python frameworks to generate synthetic clinical and operational datasets.
- Create SDTM- and ADaM-compliant datasets for downstream testing (data transformation, analysis, reporting).
- Generate domain-specific datasets (adverse events, lab results, demographics, drug exposure) with variability and referential integrity.
- Build connectors for Define-XML, Pinnacle21 validation, and statistical workflows.

AI/ML Application in Data Generation

- Apply generative AI (LLMs, GANs, diffusion models) to simulate realistic clinical case scenarios.
- Build synthetic patient journeys for eCOA, EDC, CTMS, LIMS, and PV systems.
- Automate rare/complex condition generation for system stress testing.

Compliance & Data Governance

- Ensure datasets comply with GxP, 21 CFR Part 11, HIPAA/GDPR.
- Implement data anonymization/obfuscation while retaining statistical relevance.
- Maintain validation documentation for audit and inspection readiness.

Collaboration & Integration

- Work with Clinical Data Management, Biostatistics, Pharmacovigilance, and Quality/Compliance teams.
- Integrate test data generation into CI/CD pipelines and validation environments.
- Support SMEs in assessing AI-generated datasets for regulatory acceptability.

Required Skills & Qualifications

- 5+ years of experience in software engineering, with 2–3 years in clinical/life sciences data, synthetic data, or CDISC standards.
- Strong Python expertise (pandas, NumPy, scikit-learn, PyTorch/TensorFlow, LangChain, etc.).
- Experience generating synthetic clinical trial data or working with CDISC standards (SDTM, ADaM, Define-XML).
- Familiarity with clinical data management systems (Medidata Rave, Veeva CDB, Oracle InForm, etc.).
- Understanding of GxP/21 CFR Part 11 compliance and regulated data handling.
- Knowledge of test automation frameworks (PyTest, Robot Framework) and validation tools (Pinnacle21).

Preferred Qualifications

- 7–10 years overall experience in Python/AI engineering, with significant exposure to clinical trial systems.
- Experience with EDC, CTMS, PV, LIMS, eCOA systems.
- Knowledge of SAS or R in clinical/statistical workflows.
- Hands-on experience with cloud (AWS, Azure, GCP) for secure AI/ML deployment.
- Familiarity with validation documentation & inspection readiness in pharma.

Work Timings: US (Full US Shift/ Up to 2PM ET)

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