Senior Machine Learning Engineer

AI search solution across 15+ brand help centers, providing search results from 400+ brand websites and knowledge articles spanning multiple countries, markets, domains, and languages, enabling consumers and healthcare professionals to resolve queries independently, reducing cost and reliance on human agents.

• Large-scale web crawling from 400+ brand websites across multiple countries, markets, domains, and languages. Automated scraping using Scrapy, structure-aware information extraction from leaflets using Azure AI Document Intelligence, data ingestion to Azure Blob Storage, and updating vector and keyword indexes in Azure AI Search for real-time, high-relevance retrieval and RAG-ready content delivery.
• Providing robust search, autocomplete, and suggestion APIs from Azure AI Search directly to the frontend team for seamless integration.
• Agentic RAG Agent provides streaming responses along with search results — similar to a Google Search experience with AI Overview (as shown in demo).
• LLM-as-a-Judge evaluation framework with multiple judges evaluating answers across different scenarios — disclaimer compliance, groundedness, response consistency, and relevance — ensuring quality and safety of generated responses.

Procurement Contract Intelligence

AI-powered, RAG-based (Agentic-RAG) contract intelligence platform that analyzed 11,000+ Contract IDs and 30,000+ contracts covering ~$7B third-party spend.

• Productionized modular workflows with Databricks Asset Bundles, integrating Azure Document Intelligence, Unity Catalog, and model serving endpoints along with automated deployment of Databricks App.
• Built CI/CD pipelines with GitHub Actions for automated, rollback-ready workflows, deployments, and GitOps-based orchestration.
• Agentic RAG with access to multiple tools — vector search index, SQL Toolkit, and custom Python functions working as tools for the main AI Agent — enabling deep research across contracts.
• Enabled faster contract review with deep research functionality, improved compliance visibility, and measurable time-cost savings across procurement and business teams.

Commercial Tech — Marketing Mix Models

MLOps framework for Marketing Mix Models using Databricks Bundles, Unity Catalog, and GitHub Actions for scalable, repeatable modeling of brand and market-level sales drivers. Built robust CI/CD workflows with linting, bundle validation, pre and post semantic versioning, and automated Databricks job orchestration across Dev/UAT/Prod. Enabled dynamic, market and brand specific task generation at runtime, versioned model and data persistence in Unity Catalog, reproducible deployments via explicit semantic release tags, with outputs seamlessly refreshed in Power BI for stakeholders to optimize global marketing spend.

MLOps and Agentic-RAG Foundation

Comprehensive MLOps template for Databricks leveraging GitHub Actions to automate CI/CD pipelines, including code linting, testing, environment setup, and seamless deployment of Spark jobs, such as model training, validation, and deployment, resulting in significantly enhanced workflow efficiency and reduced deployment times. Delivered standardized framework code and detailed documentation, reused across Help Center, Contract AI, NRM, NBA, QSC, and Commercial Tech projects.

Haleon GenAI Assistant

Architected and developed an enterprise-grade, multi-team GenAI platform integrating FastAPI, React, Azure OpenAI and Azure Cloud Services to enable secure, intelligent data access across Finance, Procurement, and Help Center from scratch.

• Built team-specific AI agents and modular tool frameworks using LangChain and LangGraph for contextual data retrieval.
• Enhanced retrieval quality through semantic ranker with multilingual support and hybrid search using text and vector search in Azure AI Search.
• Engineered a scalable, structure-aware document processing pipeline using Azure AI Document Intelligence with automated GitHub Actions workflows.
• Experimented with MCP (Model Context Protocol) client–server architecture for distributed tool orchestration across databases and AI services.
• Optimized chat architecture for sub-second latency through asynchronous processing, containerized deployment, and scalable microservice design.

Asset Vision

Designed and implemented a robust CI/CD pipeline with GitHub Actions to build and publish Docker images to GitHub Container Registry (GHCR) and Azure Container Registry (ACR), enabling automated deployment to Azure Web App and microservices on Kubernetes cluster for scalable, secure and reliable application management across environments. Applied same approach to streamline deployments in other RAG based projects.