Hussain Baig

-Designed and deployed production-grade Retrieval-Augmented Generation (RAG) systems using Azure OpenAI and Azure Cognitive Search, enabling accurate, source-grounded responses over large healthcare and academic document collections. -Built NLP pipelines for information extraction, document parsing, semantic chunking, and data labeling, supporting downstream AI tasks such as clinical Q&A, examination content generation, and analytics. -Developed AI-powered automation tools and LLM driven workflows using Python, FastAPI, and LangChain, transforming manual, knowledge-heavy processes into scalable AI services. -Led the development of AI-driven healthcare chatbots for institutional use, focusing on reliability, context accuracy, and safe handling of medical information. -Worked on an AI-based question generation system for the Aga Khan Examination Board, enabling automated creation of curriculum-aligned assessment questions from structured and unstructured educational content. -Integrated AI components into backend systems and APIs, ensuring production readiness through robust data handling, modular architecture, and performance-conscious design. -Contributed to the integration of PACS-based medical imaging workflows, enabling efficient AI-assisted analysis of X-ray reports by combining structured metadata, extracted radiology text, and retrieval-based reasoning. -Worked extensively with structured and unstructured healthcare data, applying validation, preprocessing, and quality checks to ensure accuracy, scalability, and system reliability in sensitive domains.

-Contributed to the development of distributed systems and enterprise web applications using .NET Core and Windows Forms, supporting scalable client-server architectures. -Maintained and enhanced large production codebases, focusing on performance optimization, stability improvements, and systematic bug resolution. -Designed and optimized real-time dashboards for business intelligence and operational monitoring, enabling improved visibility into system and data performance. -Collaborated on the architecture and development of a new product, working closely with cross-functional teams to ensure scalability, maintainability, and clean system design. -Supported backend development for a Node.js-based mobile application, including API development and database integration. -Led the design and management of relational and NoSQL databases using SQL and MongoDB, ensuring data integrity, security, and efficient query performance. -Gained hands-on exposure to DevOps and CI/CD workflows, contributing to automated deployments, environment configuration, and basic monitoring processes. -Worked with AWS services to support cloud-based infrastructure, gaining experience in performance optimization and cost-aware resource usage. -Built internal Python-based automation tools to streamline repetitive operational tasks, improving development efficiency and system workflows.

-Contributed to the development of backend components using .NET Core within a client-server architecture. -Implemented multi-threaded application logic to support concurrent processing and improve system responsiveness. -Worked with Entity Framework for database access, schema management, and CRUD operations. -Assisted in integrating RabbitMQ for asynchronous message queuing and Redis for basic caching use cases. -Built a complete CRUD-based backend service as part of the internship project, applying clean coding and API design principles. -Gained practical exposure to Node.js and Express for building RESTful backend services.

-Contributed to the development of a custom online conference booking platform, supporting scheduling, user management, and backend workflows. -Worked remotely within a distributed, cross-functional team, coordinating with designers, stakeholders, and clients to deliver production-ready solutions. -Managed technical requirements, timelines, and client communication, gaining hands-on experience in project ownership and delivery.

-Developed Python scripts for web scraping and data collection, supporting internal marketing and analytics workflows. -Built basic ETL pipelines to extract, transform, and structure data from multiple sources for downstream processing. -Worked closely with the manager to understand business requirements and translate them into simple, functional Python-based solutions.

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