Mohammad Dawood Hussain

Architecting enterprise AI platforms, distributed backend systems, and digital manufacturing solutions supporting global pharmaceutical operations — Enterprise MES.

• + Architected a production-grade pharmaceutical Recipe Authoring Agentic AI platform using LangGraph, Amazon Bedrock, RAG, MCP/tool calling, Human-in-the-Loop workflows, and LangSmith-based observability — reducing recipe-authoring effort from 4 months to 10 days.
• + Architected MCP-based semantic retrieval using AWS Aurora PostgreSQL/pgvector, enabling AI agents to discover and retrieve relevant enterprise configurations through vector similarity search.
• + Built an ETL pipeline to vectorize enterprise configurations and implemented a resilient three-tier retrieval strategy across site-specific and global knowledge bases.
• + Eliminated 12,000+ engineering hours annually by designing a distributed Manufacturing Validation Platform executing automated regression and load testing across multiple MES environments.
• + Led architecture and technical design for enterprise AI platforms, partnering with business, site stakeholders, and senior leadership; established a continuous product feedback loop and presented architectural trade-offs and demos to drive rapid product evolution.
• + Enabled natural-language analytics across 30+ enterprise manufacturing databases via a production-grade Text-to-SQL AI platform using semantic retrieval, vector databases, SQL validation, execution guardrails, and LLM-generated summaries.
• + Reduced regulated software validation effort from hours to minutes (40% improvement) with an AI-powered test script generation platform leveraging historical validation assets, RAG, and few-shot prompting.
• + Reduced critical API response time by 78% (32s → 7s) through SQL query optimization, indexing redesign, stored procedure tuning, and execution plan analysis.
• + Modernized a proprietary enterprise desktop application by reverse-engineering SQL execution patterns and building scalable Node.js REST APIs enabling full workflow automation.
• + Collaborated with the Chief Digital Architect to review enterprise architecture, validate technical designs, and align AI platform implementations with organizational engineering standards.

ENVIRONMENT — C#, Python, FastAPI, FastMCP, React, Node.js, SQL Server, PostgreSQL, AWS, Amazon Bedrock, LangGraph, LangSmith, Azure OpenAI, Docker, ECS, GitHub Actions, Redis, Milvus, pgVector

Led the architecture and development of cloud-native backend platforms for large-scale energy forecasting, utility analytics, and enterprise digital transformation initiatives serving North American utility providers.

• + Improved production incident diagnostics by 40% by architecting an asynchronous observability platform using distributed event processing, centralized logging, and telemetry pipelines.
• + Reduced cloud migration latency from 120 seconds to under 10 milliseconds by identifying infrastructure bottlenecks and redesigning AWS networking, routing, and application communication layers.
• + Designed high-performance notification and email orchestration microservices processing large-scale asynchronous workloads with improved reliability and scalability.
• + Improved gas demand forecasting accuracy by 15% by developing ML.NET-based predictive models supporting operational planning and reducing distribution wastage.
• + Partnered with client architects and product stakeholders to translate business requirements into scalable cloud-native platform architectures.
• + Delivered cloud-native REST APIs and CI/CD pipelines using ASP.NET Core, Azure DevOps, Docker, and SQL Server following secure coding and DevOps best practices.

ENVIRONMENT — C#, ASP.NET Core, ASP.NET MVC, Azure PaaS, SOA, Microservices architecture

Developed enterprise applications across healthcare, finance, insurance, and utility domains using Microsoft technologies while progressively taking ownership of architecture, backend design, and technical leadership.

• + Reduced enterprise batch processing time from 2 hours to under 1 minute by designing Azure Functions-based event-driven processing pipelines.
• + Developed scalable backend services and REST APIs supporting high-volume enterprise billing, reporting, and operational workflows.
• + Built enterprise monitoring and operational dashboards improving production visibility and reducing manual support effort.
• + Designed authentication and Microsoft Graph integrations enabling secure enterprise collaboration and workflow automation.
• + Automated recurring business processes using Windows Services, background jobs, scheduled tasks, and reporting solutions.