Tapan Guru

AI/ML Engineer with 4.5+ years of experience building and operating Generative AI, Machine Learning, and Azure cloud solutions. Hands-on experience across RAG, Agentic RAG, Multi-Agent Systems, LLM Orchestration, MLflow, MLOps, CI/CD, Monitoring, Observability, and AI Operations. Delivered measurable impact including 80% lower manual query effort, 60% fewer exception-handling cases, 50% faster cloud provisioning, and document extraction accuracy improvement from 65% to 90%.

AI/ML Engineer at Tiger Analytics (2025-09 – Present)

• Architected and delivered an enterprise Generative AI platform for knowledge discovery, contextual summarization, and AI-assisted workflows across business functions.
• Designed and deployed Multi-Agent AI and Agentic RAG pipelines using LLM orchestration for reasoning, task routing, and structured query execution.
• Engineered and optimized RAG pipelines across retrieval, grounding, and context strategies to improve response accuracy and relevance.
• Implemented LLM evaluation frameworks and guardrails to measure response quality, enforce safety controls, and improve production AI reliability.
• Built secure Azure-native AI infrastructure integrating AI services, Cosmos DB, Blob Storage, RBAC, authentication, and access controls.
• Developed and productionized FastAPI backends and Azure Functions with Docker-based deployments, automated CI/CD, deployment workflows, monitoring, and production support.
• Established AI observability and operational controls covering monitoring, logging, RBAC, reliability checks, and production support to strengthen service operations.

Associate Consultant at EY India (2023-09 – 2025-09)

• Developed a GPT-based natural language-to-SQL solution that reduced manual query effort by 80%, enabling faster AI-assisted access to enterprise data.
• Implemented MLflow experiment tracking and standardized prompt engineering practices to improve reproducibility, evaluation, version control, and AI lifecycle management.
• Engineered Azure Databricks data pipelines for production AI workloads, supporting high-volume data processing and real-time query execution.
• Automated CI/CD and deployment workflows for AI and data solutions, improving release stability and reducing rollback incidents.

Senior Analyst at EY India (2022-07 – 2023-09)

• Developed Python-based production data pipelines achieving up to 90% processing accuracy, supporting reliable downstream workflows.
• Built event-driven Azure Functions architectures that reduced scheduling issues by 35%, improving operational reliability.
• Automated business workflows using Azure Logic Apps, reducing operational delays by 25% and improving process reliability.
• Managed ingestion of 5,000+ records weekly into cloud storage systems, ensuring reliable data availability for downstream analytics workflows.
• Developed Power BI dashboards for operational KPI monitoring, performance tracking, and analytics-driven decision support.

Intern at EY India (2022-02 – 2022-06)

• Automated reporting pipelines, reducing report generation time by 50% and improving operational efficiency.
• Implemented data validation frameworks to improve data quality, reliability, and consistency across operational workflows.

Bachelor of Engineering in Electronics and Communication Engineering – Siksha 'O' Anusandhan University (2018 – 2022)