Abi Vignesh

I’m a high-agency Senior GenAI & Data Engineer with 8 years owning production AI platforms and large-scale data systems. I focus on multi-agent LLMs, RAG, and cloud-native infrastructure to deliver accurate, context-aware outcomes.

In my current role, I’m building a multi-agent enterprise data platform for conversational access to distributed enterprise data—dynamically selecting sources and orchestrating end-to-end query execution. I also implemented a production LLM observability framework with Langfuse and LiteLLM for tracing, cost/latency monitoring, prompt experimentation, and data-driven workflow optimization.

Previously, I architected and owned a production-grade multi-agent AI platform using Claude MCP, Gemini Native RAG, and agentic orchestration to unify enterprise knowledge for structured and unstructured conversations. I delivered AI-driven PDLC automation (reducing manual effort by 80%+) and production applications for conversational enterprise search and extraction workflows (reducing manual operations by 40% while maintaining 99.9% uptime), including an end-to-end MVP launch in 4 weeks with enterprise adoption.

I bring strong data engineering depth from marketing data products and scalable ETL pipelines across cloud migrations. I’ve built 20+ PySpark/Hive/Teradata pipelines for ~200 GB daily datasets, migrated 150+ pipelines to Google Cloud Platform, and improved reliability and performance (including reducing SLA by 1 hour daily and saving 250+ analyst hours annually). I’m recognized with the DRIVE Rising Star Award and President’s Award (Team NITRO), and I mentor engineers while championing production readiness, evaluation, and best practices.