• Developed ServiceNow Cloud Server-side scripts in JavaScript for Data Analytics & Reporting using GlideRecord API and HistoryWalker API, and Tickets Data Manipulation.
• Developed Python Flask Microservice to store ServiceNow Incidents and Knowledge Base Articles into MySQL database for Data Analytics & Reporting. 
• Developed Python Flask Microservice to quickly perform Clustering of large volume of consistently increasing Incidents data for Ticket Pattern Prediction using SBERT Fast Clustering algorithm with Transformer-based LLM for proactive identification of potential major incident cases. 
• Implemented Semantic Search on ServiceNow Knowledge Base Articles for suggesting possible solutions for Incidents using Facebook AI Similarity Search (FAISS) Vector Database with Haystack, SBERT Sentence Transformer and Retrieval Augmented Generation (RAG) using Embedding Retrievers, deployed as Python Flask Microservice.
• Implemented Ticket Activity Summarization of ServiceNow Incidents Work Notes, Comments and related Knowledge Base Articles using Hugging Face Transformers-Summarizer to help triage analysts quickly understand all the steps the Case has gone through so far, hence reducing the Mean time to resolution; deployed as Python Flask Microservice.
• Implemented Classification of Incidents under user-defined labels by training Rasa Natural Language Understanding (NLU) and generating data analytics reports; deployed as Python Flask Microservice.
• Eliminated Manual ServiceNow Ticket Assignments by assigning the tickets to the appropriate support executive using Ticket Classification & Clustering data, and user defined rule sets; implemented as Python Flask Microservice being consumed by ServiceNow.
• Implemented Sentiment Analysis of the Ticket Caller Comments by training Rasa NLU for determining the provided resolution accuracy and Customer Satisfaction Level.
• Developed Microservice to perform Sarbanes-Oxley (SOX) compliance auditing of Unit Test Plans and Results for every Project and Defect in every Release cycle, by extracting the current release cycle Projects details from MongoDB and related Story/Defects details from VersionOne API; and send reports of compliance issues via email and Ms Teams notifications using Webhooks.

• Completed a working POC on DevOps CICD and presented it to the Customer CEO and CTO.
• Developed SSIS package for SSISDB Catalog Log Data Analysis & Reporting using Slowly Changing Dimension.
• Developed SSIS ETL packages for extracting, cleaning, transforming and loading data from Mainframe extracted Flat Files into Microsoft SQL Data Warehouse.
• Developed Complex ETL Packages using Microsoft BI SSIS to extract data from staging tables to partitioned tables with Incremental Load. Created databases and schema objects including tables, indexes and applied constraints, connected various applications to the database and written functions, stored procedures and triggers.
• Developed C#.Net Application to request and retrieve Customer Credit Score Data from Experian, to determine the Risk Score required for new credit line approval.  
• Developed C#.Net application to connect Microsoft Team Foundation Server (TFS) 2017, (rebranded as Azure DevOps Server) with the HP Application Lifecycle Management (ALM) for invoking Functional Tests in ALM from TFS and defects handling.
• Developed a Defect Monitoring System using C#.Net for Defect Data Analysis & Reporting of possible SLA Compliance cases.
• Developed C#.Net Bulk Sample Data File Generator application capable of producing extensive sets of sample input data files containing unique records and offering numerous customization options for SQL/SSIS package Performance Analysis. The application has garnered significant praise from developers across different organizations for its functionality and versatility.
• Developed Associate Management System (AMS) using ASP.Net/C#/SQL for managing Accommodation allocation and training batch tagging for new joiners.

Developed a Speech-based Virtual Assistant System on C#/ASP.Net/MsSQL using Microsoft Speech API for Speech Recognition, OpenCV for Face Recognition and Google Speech-to-Text API for sending voice commands from any IoT device with a Web browser to perform actions on the connected devices with the App installed. Hosted the Web application and Web service on Cloud.