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Sayantan Dasgupta

Founding Engineer · Full-Stack · AI Systems

© Sayantan Dasgupta

Experience

Work Experience

Founding Engineer

Renben Technologies, Pte. Ltd.

May 2025 - Present
  • Re-architected a production library management system from a monolithic Next.js codebase to a modular NestJS service layer, improving scalability, endpoint performance, and long-term maintainability for a platform serving schoolchildren across rural China
  • Owned Azure cloud infrastructure end-to-end using Terraform — provisioning, scaling, and high-availability configuration for production workloads
  • Engineered a dynamic form builder and corresponding mobile frontend for a Japan-based market research firm, enabling fully configurable survey workflows delivered to end-users at scale
  • Contributing to the architecture and implementation of an internal AI product currently in pre-launch stealth
  • Bridged engineering and client stakeholders as the primary customer-facing contact — owning relationship management, expectation-setting, and delivery alignment

Consulting Software Engineer

Caravel Labs, Inc.

Dec 2024 - Apr 2025
  • Built a React-based Azure DevOps extension; deployed to 120+ teams with 100+ monthly active users within 30 days of release
  • Enabled real-time performance tracking via native Azure APIs with customizable time ranges (1 week–6 months)
  • Automated DORA metric calculations to benchmark team performance and drive data-driven improvements

Systems Engineer

Tata Consultancy Services Ltd. (TCS)

Oct 2023 - Nov 2024
  • Redesigned Python-based ETL pipelines within CI/CD workflows, automating manual data warehousing procedures and improving job efficiency by 90%
  • Provisioned and maintained Azure infrastructure via Terraform for multi-service deployments
  • Designed FlexDeploy-based deployment pipelines for enterprise applications, enforcing compliance checks and reducing failed deployments

SDE Intern

MindWebs Ventures, Pvt. Ltd.

Nov 2021 - Jan 2023
  • Developed an offline-first backend system using Node.js and TypeScript to collect and process patient data during remote medical camps for diabetic retinopathy screening.
  • Engineered a data pipeline with Redis for local storage and conditional synchronization to a global MongoDB database, ensuring seamless offline-to-online data transfer.
  • Integrated a background machine learning model to analyze retinal images and predict disease severity; built a lightweight EJS-based frontend to support intuitive, field-friendly usage.