• Designed and implemented a production agent orchestration platform enabling LLM-driven workflows across enterprise systems.

• Built backend frameworks for tool-using LLM agents, supporting reasoning loops and integration with internal APIs and knowledge retrieval systems.

• Developed event-driven agent pipelines on AWS to ingest and normalize real-time events from external platforms into internal workflows.

• Implemented observability and tracing for agent execution, tracking tool calls, latency, and failure recovery across distributed services.

• Designed and operated distributed search infrastructure for multi-tenant enterprise knowledge systems, enabling scalable retrieval across highly connected datasets.

• Built large-scale indexing pipelines and query-serving APIs using Python and FastAPI powering OpenSearch-based retrieval systems handling 200K+ daily queries with 99.9% uptime.

• Reduced search latency by 35% through query optimization, asynchronous I/O, connection pooling, and caching strategies.

• Implemented hybrid lexical–semantic retrieval architecture, integrating embedding-based semantic search with traditional inverted-index ranking.

• Instrumented observability and performance monitoring for search services, tracking latency, throughput, and reliability metrics across distributed retrieval pipelines.

• Developed a Generative Adversarial Network (GAN) to synthetically generate satellite data, enhancing data availability for research.

• Conducted data analysis to identify trends and insights from satellite imagery.

• Assisted in preparing technical reports and presentations for stakeholders.

• Evaluated machine learning models and fine-tuned parameters to optimize results.