Venkatesh G

Designed and deployed a multi-agent L2-triage platform for a healthcare client, reducing investigation time from hours to minutes and supporting production tickets across Autosys, SQL, file servers, and ServiceNow. Architected secure MCP tool servers and built a GraphRAG-based intent routing and LangGraph graph compiler to convert SOP plans into deterministic, auditable workflows.

Built and deployed LangGraph agents for Chief of Staff, StandUp, Market Research, and information-gathering workflows using stateful orchestration and plan-and-execute patterns. Developed RAG applications with Pinecone/FAISS and Azure OpenAI embeddings, and engineered NLP pipelines for PII masking, NER, and entity linking; fine-tuned BERT and RoBERTa models on Vertex AI.

Built and maintained PySpark and Scala ETL pipelines processing 100GB+ daily and implemented near-real-time ingestion with Spark Streaming and GCP Pub/Sub. Optimized warehouse models and storage design to reduce storage costs while improving query performance, and delivered curated datasets that reduced insight turnaround time.

Built a Python recommendation model with custom feature engineering and designed Spark/Kafka ingestion pipelines for large-scale structured and unstructured data. Performed exploratory analysis, automated model evaluation, and developed dashboards that improved delivery of actionable business insights.

Completed an M.S. in Applied Computer Science from Northwest Missouri State University from August 2021 to May 2023.

Completed a B.E. in Electronics & Communications at Andhra University from July 2015 to May 2019.