Nagendra Hegde

About Nagendra Hegde

Data Engineer and GenAI Engineer with 5+ years building and running AI and data systems used by real teams in production.I work across both tracks. On the data side building ETL/ELT pipelines, lakehouse architecture, and data warehouses on AWS, Snowflake, and Databricks, and on the AI side building LLM applications, RAG (Retrieval-Augmented Generation) pipelines, and agentic AI workflows using LangGraph, OpenAI APIs, and pgvector.My experience spans financial services, healthcare, and payments, with a focus on systems that are reliable, scalable, and easy to maintain. I have strong hands-on experience with Python, PySpark, SQL, dbt, Apache Spark, SageMaker, and MLOps, and I enjoy working closely with product, data, and engineering teams to turn business problems into well-designed data and AI solutions.Open to Data Engineer, Senior Data Engineer, AI Engineer, and GenAI Engineer roles.

Experience

1. Genai Engineer

   JPMorganChase

   Nov 2024 — Present · US

   Built and deployed production RAG (Retrieval-Augmented Generation) pipelines connected to internal financial, compliance, and market data sources using LangGraph agents, OpenAI embeddings, and pgvector, improving response accuracy by 25% and reducing follow-up queries across thousands of daily internal requests.• Designed and deployed agentic AI workflows and LLM applications in Python to automate multi-step research and data gathering for advisory and risk teams, cutting manual review time by 30-40% and reducing turnaround time by 20%.• Engineered batch and near-real-time data pipelines using PostgreSQL, DynamoDB, OpenSearch, and Redis to manage vector embeddings, metadata, and high-volume queries across multiple AI-driven tools with semantic deduplication and data observability monitoring.• Deployed machine learning pipelines and LLM services on AWS using SageMaker and EKS with full CI/CD automation, enabling stable model releases, drift monitoring, and model lifecycle management in production.• Collaborated cross-functionally with governance and compliance teams to implement logging, access controls, model monitoring, and data contracts, ensuring AI solutions met internal risk, audit, and regulatory compliance requirements.• Skills: Python, LLM Applications, RAG, LangGraph, pgvector, AWS, SageMaker, EKS, PostgreSQL, DynamoDB, OpenSearch, Redis, ETL Pipelines, Data Pipelines, Data Engineering, Machine Learning, MLOps, CI/CD, Data Observability, Agentic AI, Vector Databases, Feature Engineering, Data Governance

Education

• Northeastern University

  Master's degree, Applied machine intelligence

• Vivekananda College of Engg. & Tech., PUTTUR

  Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering

  2015 — 2019