Hemendra Jampala
I’m Hemendra Jampala, a Generative AI/ML Engineer with 9+ years of experience building production-grade machine learning and LLM-powered solutions.
About
I’m Hemendra Jampala, a Generative AI/ML Engineer with 9+ years of experience building production-grade machine learning and LLM-powered solutions. I specialize in designing and deploying chatbot and agentic AI systems, along with advanced retrieval architectures like RAG and graph/agentic RAG for real-world, customer-facing workflows.
Throughout my career, I’ve built end-to-end pipelines and APIs using Python, PySpark, FastAPI, and cloud-native platforms such as Azure AI/ML and AWS services. I enjoy working across the full ML lifecycle—data engineering, model development and evaluation, and scalable deployment—while delivering measurable business impact through systems like churn prediction, enterprise-integrated conversational assistants, and performance-optimized order APIs.
- 9 years' experience
- Joined September 2026
Industry experience
- Healthcare
- Financial Services
- Retail
- Professional Services
Work experience
Designed and developed an AI-powered conversational chatbot and data-driven solutions for retail pharmacy. Implemented retail analytics automation workflows using LangChain and LangGraph and built scalable chatbot integrations using Google ADK with secure enterprise backend connectivity. Developed an end-to-end customer churn prediction system using transactional and prescription data, and deployed high-performance RESTful APIs (FastAPI) for real-time Pick & Pack order access. Containerized applications with Docker, added robust logging/error handling and monitoring for availability, and optimized API latency for high-traffic usage. Built scalable data pipelines with PySpark and Spark SQL, orchestrating large-scale processing using Azure Data Factory and Databricks. Trained and optimized machine learning models (Logistic Regression, Random Forest, Gradient Boosting) with time-based validation and evaluated using ROC-AUC and Precision-Recall metrics.
Worked on internal transfer application modules, including Internal Transfer and Manage Credit/Debit Card components. Built and maintained Azure Data Factory pipelines using activities such as Copy, Lookup, For Each, Databricks notebooks, metadata retrieval, pipeline execution, stored procedures, and conditional logic. Performed transformations and joins on temporary tables, and loaded data into target data lakes in CSV and Parquet formats. Improved ETL reliability and automation via scheduled, event- and time-based Azure Data Factory jobs, supporting ongoing operational needs for the bank’s applications.
Delivered Annual Enrollment and New Hire Enrollment projects for UTC, supporting a Health & Welfare Benefits enrollment platform used by 10,000 employees during enrollment and onboarding. Led end-to-end SDLC activities including design, technical documentation, sprint planning, code reviews, deployment support, and on-call production operations. Developed and enhanced Java Spring MVC modules for benefits enrollment functionality such as health plan selection, dependent management, and life event processing. Wrote and optimized SQL for reporting and client-specific requirements, and owned release sign-off and production validation across multiple enrollment cycles, performing RCA and resolution for critical production issues to maintain reliability and performance.
Education
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