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Software Engineer with 7+ years in Full-stack, Cloud & AI
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Senior Software Engineer with 7 years of experience delivering scalable full-stack platforms across financial, e-commerce, and cloud domains. Built and shipped a production financial data processing platform handling CT600 tax form automation, HMRC compliance workflows, and AI-driven query resolution - giving me hands-on exposure to the precision, security, and reliability standards that fintech products demand. Proficient across the full stack - Go (Gin), Node.js, NestJS, Python (Flask), React, Angular - with deep expertise in AWS, Kubernetes, microservices architecture, CI/CD pipelines, and automated testing. Known for mentoring junior engineers and driving projects end-to-end from architecture to production in Agile environments.
JSPM's JIMS
Masters in Computer Application
N/A – June 30, 2020
Modern College
Bachelors in Computer Application
N/A – June 30, 2017
Cloudamize
Product Software Engineer
February 1, 2025 – Present
India
GateAl Pvt. Ltd
Senior Software Engineer
June 1, 2024 – January 1, 2025
India
QuadLogix Technologies Pvt. Ltd
Senior Software Engineer
October 1, 2021 – June 1, 2024
India
Aloha Technologies Pvt. Ltd
Software Developer
August 1, 2019 – October 1, 2021
India
YASM Pvt. Ltd
Intern
February 1, 2019 – July 1, 2019
India
Cloud Migration & Optimization Platform
February 1, 2025 – June 30, 2026
Architected an AI-based resource grouping system in Python that ingests large-scale cloud infrastructure inventory, constructs relationship graphs, and applies community detection (Leiden algorithm) to cluster similar resources - improving downstream recommendation pipeline accuracy. Developed Go (Gin) backend services for the CDW recommendation engine - designed RESTful APIs, implemented business logic for resource mapping, and built high-performance data transformation pipelines processing large-scale cloud inventory datasets. Built concurrent Go services leveraging goroutines and channels for parallel processing of cloud inventory ingestion and recommendation generation - significantly improving throughput on large datasets. Deployed and managed containerized microservices on Kubernetes (AWS ECS) - authored deployment manifests, configured resource limits, managed IAM roles, and handled production debugging via CloudWatch logs and metrics. Worked extensively with PostgreSQL at scale - complex queries on nested JSON data, index design, and query path optimization for high-volume datasets. Wrote unit tests with Jest across critical code paths. Improved CI/CD pipelines with OIDC-based GitHub Actions authentication and SonarQube integration.
WolffTax - Financial Data Processing & AI Tax Platform
June 1, 2024 – January 1, 2025
Developed WolffTax, a financial platform automating income tax calculations, CT600 tax form processing, and HMRC compliance query resolution - reducing user processing time by 30% through efficient data retrieval and dynamic document referencing. Built high-performance Go (Gin) microservices handling document ingestion, tax computation orchestration, and async job dispatching - enabling fast, concurrent processing of user-submitted tax forms and financial datasets. Built secure backend services in NestJS and Node.js handling sensitive financial data - income tax computations, document parsing, and HMRC manual lookups - with OOP-based service architecture, dependency injection, and strict data integrity requirements throughout. Enabled users to upload CT600 tax forms for automated income tax calculation; responses cited referenced HMRC manuals with relevant PDF sections dynamically highlighted for clarity and auditability. Implemented the Knowledge Scope feature - users upload PDFs or DOCX files to train the RAG system on custom financial datasets; scopes are saved, reusable, and attachable to chat threads. Implemented horizontal scaling with ASG for concurrent training jobs, processing 50GB of files in under 30 minutes. Reduced cloud operational costs by $10K annually through optimized AWS configurations. Stored embeddings in Pinecone using OpenAI embeddings for high-performance vector search; built the RAG pipeline in Python using Flask and LangChain.
Marketrise - Marketing Campaign Management Platform
October 1, 2021 – June 1, 2024
Led end-to-end development of Marketrise, a centralized marketing campaign management platform for SMBs - enabling planning, execution, and KPI tracking across online, offline, print, email, and social media channels from a single dashboard. Built a responsive React frontend with TypeScript - campaign dashboards, budget allocation views, and real-time KPI monitoring widgets with full type safety. Wrote unit tests with Jest for service and component logic, and end-to-end tests with Cypress covering critical user journeys including campaign creation, budget setting, and KPI monitoring. Built a highly scalable serverless backend using NestJS, Node.js, AWS Lambda, and API Gateway. Deployed application services on Kubernetes for consistent, scalable container orchestration. Integrated CloudFront with S3 for fast static asset delivery. Provided strategic leadership to a team of junior developers from requirements through production delivery.
Trend Engine - E-commerce Analysis Platform
August 1, 2019 – October 1, 2021
Contributed to a fashion retail intelligence platform scraping hundreds of branded websites (Zara, H&M, Forever 21) to collect and maintain inventory, pricing, and SKU data at terabyte scale. Built dynamic Angular UIs - search-as-you-go interfaces, trend dashboards, Gap Analysis widget, Color Wheel widget, and a Visual Search feature for image-based inventory matching. Developed REST APIs using Node.js and Express.js, and wrote specialized Elasticsearch services powering the platform's analytical and search capabilities.
ETL Data Ingestion Tool
August 1, 2019 – October 1, 2021
Developed a config-based ETL tool in Python and Flask to automate ingestion pipelines from Amazon Redshift to Elasticsearch - eliminating manual intervention via Apache Airflow DAG scheduling. Wrote complex SQL transformation queries, created new Elasticsearch indices, and built fully automated scheduling workflows.
Instabikes - Bike Booking Platform
February 1, 2019 – July 1, 2019
Independently designed and delivered a full-featured bike booking platform covering the complete rental lifecycle - inventory, customer management, bookings, payment gateway integration, OTP authentication, and admin panel. Deployed on a VPS with Nginx as reverse proxy and automated cron jobs for database backups.
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit through diverse project experience across financial, e-commerce, and cloud domains. Their involvement in team leadership, mentoring, and end-to-end project delivery aligns well with a collaborative and growth-oriented culture. The breadth of technologies and methodologies used (Agile, DevOps) suggests adaptability and a continuous learning mindset, which are valuable for cultural integration.
Soft Skills & Operational Fit
The candidate's resume highlights strong leadership in team settings, mentoring junior developers, and driving projects from architecture to production in Agile environments. This indicates a proactive, collaborative, and results-oriented operational fit. The focus on cost optimization and security also suggests a practical and responsible approach to engineering.