Venkat Bezawada

I’m a software engineer with 4+ years in clinical data engineering, focused on SDTM validation, data quality automation, and Python-based reporting for pharma clients including AbbVie. I’m now actively transitioning into AI engineering by building on my context and workflow experience in real, regulated environments.

At Cognizant Technology Solutions, I automated clinical data quality reporting with Python (Pandas, Jinja2, SQL), cutting manual effort by 50%. I also maintained SDTM validation scripts across 10+ clinical domains and implemented data quality rule functions in eClinical platforms, including SPID-level intersection logic for Enrollment Failure eCRF form validation.

I built tools that make validation scalable—like a SAAMA Validation Code Generator that auto-generates domain-specific validation code (Pandas, PySpark, Polars) from structured inputs with error logging and Excel export. I also contributed to integration workflows connecting EDC, CTMS, Medidata, and VEEVA via the SAAMA Life Science Hub.

On the AI side, I’ve started using the Claude API to create small agentic workflows that automate repetitive reporting and validation tasks, pairing that with hands-on learning in prompt and context engineering. I’m currently exploring the Anthropic Claude API and LLM internals, with coursework in Gen & Agentic AI and early-stage agents already deployed to support my current team.