Rajvardhann Singh
Software Engineer @SurveyMonkey || Backend & Distributed Systems || Java, Python, System Design || NIT Raipur’25
Bengaluru
2+ years of work experience
Jan 20268 mosPresent
Hybrid
1. Shipped an end-to-end recurring profiling system for 200M+ panelists, replacing the legacy one-time-only model with a calendar-window-based re-profiling engine (quarterly refreshes); designed and implemented staleness-detection APIs, four-path submission handling (first-time/recurrent × core/advanced), threshold-cycle payment deduplication, and per-segment per-window reward logic.
2. Built an email validation workflow for Android/iOS signups using ZeroBounce, reducing fraudulent signups by ~40% while maintaining <150ms latency across 30K+ signups/month.
3. Owned migration from single-call survey API integrations to orchestrated multi-API workflows across 3 different microservices, maintaining functional parity and supporting 850K+ requests/day without disruption.
4. Implemented backend decision logic integrating ML-based response quality scoring while preserving trap-question precedence rules, enabling automated disqualification of ~10K low-quality survey responses daily.
Jul 20256 mosDec 2025
On-site
1. Integrated handling for Stripe & ProcessOut chargeback won/lost events into billing workflows, processing dispute outcomes and downstream state transitions.
2.Built backend workflows for refunds and subscription changes, handling prorations, tax calculations, and downstream billing updates.
3. Extended a Kafka-based event pipeline for usage-based pricing (RBP) by adding event handling logic, retries, and validations, improving reliability and auditability of revenue events.
4. Extended existing AWS SQS/SNS–backed payment orchestration workflows by integrating Stripe and ProcessOut webhook events, supporting secure tokenized invoice payments in a large-scale SaaS billing platform.
5. Upgraded Python versions across five production microservices from <3.10 to 3.12, enhancing performance, security, and long-term maintainability.
6. Implemented final invoice generation logic with multi-language support (20+ locales), ensuring accurate discounts, SKU pricing, and totals in customer-facing invoices.
Feb 20254 mosMay 2025
Singapore
1.Refactored legacy error handling in tick price CSV uploads using a centralized GlobalErrorHandler, eliminating recurring pager alerts.
2.Enhanced the file upload experience by upgrading both backend and Securities UI for downloadable success/error logs and better trade dealing traceability.
3.Resolved bank account prefix mismatches, improving data integrity and enabling accurate manual deposit linking by Ops teams.
4.Improved portfolio UX by displaying FX trade wallet balances to prevent premature submissions and enabling real-time rebate rate editing with audit logging and cache syncing.
5.Redesigned legacy audit logs to capture both old and new values for key updates, streamlining auditing and eliminating reliance on database-level queries.
Jul 20246 mosDec 2024
Gurugram, Haryana, India
1. Updated the GRIP’sandbox platform with new updated APIs, enhancing visibility of request and response interactions for external companies, and added a redirection section.
2. Created complete API documentation ensuring clarity, consistency, and ease of use for developers and stakeholders.
3. Implemented additional frontend features to support key functionalities within the Grip-Terminal-Web (Internal tool).
4. Developed a dynamic internal tool leveraging Jira data for productivity tracking across QA, App, and Product Tech teams, featuring real-time dashboards to monitor issue types. Implemented custom date filters for analysis beyond sprint cycles and designed a database to streamline productivity calculations, tracking working days, leaves, and employee details.
a. Sprint-wise Productivity Tracking: Select a sprint to track Adhocs, Incidents, Unassigned Tasks, Bugs, and developer productivity, factoring in working days, leaves, and story points assigned based on developer availability.
b. Sprint Summary: Real-time metrics including:
- Completed Story Points: Tracks total completed story points.
- Planned Tasks: Tracks tasks initially planned for the sprint.
- Bugs & Incidents: Monitors bugs and incidents reported.
- Urgent Issues: Highlights critical issues.
- Tickets Added Post-Sprint Start: Identifies tickets added after the sprint begins.
c. QA Productivity Dashboard: Tracks bugs, false bugs, and incidents categorized by root cause (operational, third-party, coding-related).
d. Week-on-Week Tracking: Tracks metrics (Monday to Friday) with customizable date ranges. Metrics include incidents, adhocs, and recurring trends for better resource allocation.
e. App Development Team Productivity: Tracks developer productivity by factoring in working days, leave days, and expected story points, giving managers insights into individual and team performance.
May 20242 moJul 2024
Bengaluru, Karnataka, India
-Automated the floor plan drawing process, reducing manual entry time from 15-20 minutes to under a minute, significantly improving efficiency and reducing errors.
- Implemented a deep multi-task neural network based on a research paper using PyTorch, NumPy, and Python, incorporating advanced mechanisms to predict room boundaries and types.
-Utilized OpenCV for image processing to refine predictions and developed algorithms for accurate room mapping in SpaceCraft(internal tool).
May 20231 moMay 2023
Bhilai, Chhattisgarh, India
Rajvardhann’s AI Stack
Education
Bachelor of Technology - BTech
National Institute of Technology Raipur
20214 yrs2025
High School Education, PCM + IT(Java)
Senior Secondary School Sector-X Bhilai
20182 yrs2020
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