Shubham Singhal

Team: Resellers – B2B Personalization and Campaigns.

• Developed and optimized the Partner Pro campaign engine to deliver tiered B2B discounts based on annual purchase behavior, increasing reseller engagement and retention.
• Implemented segmentation logic to deliver personalized offers using behavioral and transactional data.
• Engineered A/B testing pipelines using Statsig to enable data-backed experimentation and feature rollouts.
• Developed critical features like Multiple Design Submission to enhance usability for business clients.
• Integrated Zendesk for automated ticket creation to assist the customer support team.
• Built dynamic feedback forms using React Hook Form with Zod validation to ensure high-quality submissions.
• Built responsive, performant UIs with React, Tailwind CSS, Gatsby, Contentful, and deployed via Netlify.
• Developed secure backend APIs using NestJS and OAuth 2.0 for authentication and role-based access.
• Collaborated in the design and implementation phases with architects and product managers.
• Automated frontend testing with Playwright, unit testing with Jest, and built reusable components in Storybook.
• Integrated monitoring tools like Sentry and New Relic for full-stack observability.
• Architected event-driven services using AWS Lambda, SNS, SQS, API Gateway, and CloudFormation in a microservices-based monorepo setup.
• Utilized GitHub Copilot and CodeRabbit to enhance developer productivity and code quality.

Impact: Reduced deployment cycles by 30%, increased personalization-driven conversions, and improved support workflows via Zendesk.

Team: Manufacturing – Production Workflow & Automation

• Engineered end-to-end software to manage the complete production lifecycle for WebShop orders processed in in-house manufacturing units.
• Developed microservices using an event-driven architecture to track real-time phases like print, pack, and ship.
• Created dashboards to monitor production KPIs including backlog and on-time delivery, using AWS Lambda, cron jobs, and S3-based pipelines.
• Built and maintained the PDF Shop Repo to deliver detailed product specs to floor workers, enhancing process accuracy.
• Collaborated with operations teams to translate real-world production needs into scalable backend logic.
• Developed backend services using NestJS, and frontend dashboards using React, all tested with Jest.
• Deployed features using GitLab CI/CD in a version-controlled environment.

Impact: Reduced processing delays by 25%, improved floor accuracy through automation, and enabled real-time visibility for manufacturing leads.

Client: CommScope – Conversational AI and Real-Time Services

• Developed and deployed a chatbot for CommScope using Google Dialogflow, React, and Node.js, enabling real-time user interaction with company services.
• Managed context flows and session state effectively within Dialogflow to maintain seamless conversation logic and natural transitions.
• Integrated the chatbot into Slack, expanding its availability across internal channels.
• Delivered real-time service data to users via backend integration with CommScope's APIs.
• Led a team of 4 engineers, overseeing design, development, deployment, and maintenance of the end-to-end solution.
• Collaborated with stakeholders from CommScope to define user journeys, intents, and performance metrics.

Impact: Streamlined internal support, enhanced data access, and delivered scalable chatbot experience across platforms.

Client: Virtusa – Ticketing System Development

• Developed a custom ticketing system that enabled users to request and track service milestones across the lifecycle.
• Reduced customer service overhead through clear milestone tracking and improved visibility into request status.
• Integrated backend workflows using Node.js and front-end UI using React for real-time ticket visibility.

Impact: Significantly reduced customer care costs and improved service delivery transparency.

Client: AB InBev – Brewery Data & Forecasting Tool

• Built a data pipeline to collect and unify data across multiple breweries for forecasting and analytics.
• Designed and implemented database triggers, views, and scheduled cron jobs using Node.js to automate processing.
• Deployed forecasting application on Heroku to ensure scalability, availability, and operational ease.
• Created dynamic data visualizations using React charting libraries, enabling intuitive insights for business users.

Impact: Enhanced forecasting accuracy and enabled brewery teams to make real-time production and supply chain decisions.

Client: Paytm – Vendor Integration & Frontend Migration

• Integrated multiple third-party vendors into the Paytm recharge platform, enabling smooth and seamless service delivery to end-users.
• Developed and maintained API integrations to support recharge transactions and real-time user data flows.
• Collaborated with cross-functional teams to gather requirements, design solutions, and implement features ensuring high usability and reliability.
• Played a key role in migrating the Paytm web platform from Angular to React, improving performance and developer efficiency.
• Utilized Node.js, React, Angular, and JavaScript to build and support critical application features

Impact: Contributed to platform modernization and improved vendor integration scalability for Paytm’s recharge services.

Client: Munich Re & IBM Watson – Insurance & Cognitive Tools

• Developed a risk management web tool using AngularJS and .NET for Munich Re Insurance, enabling client-side risk assessments and reporting.
• Led the migration of the entire platform from .NET to AngularJS, improving overall performance, maintainability, and user experience.
• Contributed to IBM Watson’s cognitive tooling efforts by developing intelligent modules that provided users with accurate, topic-specific answers.
• Utilized Node.js, MySQL, MongoDB, and Angular to build, scale, and enhance the cognitive platform.
• Collaborated with cross-functional teams on requirements gathering, design, and quality testing to ensure platform stability and accuracy.

Impact: Accelerated platform performance, improved client-facing tooling, and strengthened IBM’s AI product offering.