Chapter 02
Experience
Career timeline from resume — fintech, e-commerce, commerce backends, agentic AI, and data engineering (Feb 2022 — present).
Fintech
Finanshels
Full Stack Developer
Remote, India
Feb 2025 — Present
Present
90%+Bookkeeping TAT reduction
- —Spearheaded development of a comprehensive Practice Management platform using Next.js + NestJS
- —Architected a production LLM-powered AI Bookkeeper reducing bookkeeping TAT by over 90%
- —Designed event-driven microservices on AWS (Lambda, DynamoDB Streams, SQS) ensuring fault tolerance
- —Delivered client onboarding, task tracking, and team collaboration workflows across the practice platform
- —Integrated LLM pipelines for automated categorization, reconciliation, and bookkeeping in production
- —Designed RAG pipelines with vector database integration for context-aware document retrieval in financial workflows
- —Automated full-cycle organizational workflows bridging sales pipelines, project management, and accounting systems
- —Architected a personalized AI Bookkeeper with Python, CrewAI, and LangChain — multi-agent orchestrator cutting TAT from weeks to under one day
- —Built a secure client portal with unified profiles, timesheet tracking, task management, and automated report delivery
- —Directed engineering operations in the absence of the VP of Engineering — CI/CD, stand-ups, and technical innovation
Next.jsNestJSTypeScriptPythonAWS LambdaDynamoDBCrewAILangChainPostgreSQL
E-commerce
The Good Glamm Group
Python Developer
Mumbai, India
May 2024 — Feb 2025
10 months
35%p99 latency improvement
40%Faster deployment cycles
- —Migrated legacy monoliths to event-driven microservices on Docker/AWS
- —Improved p99 latency by 35% on high-traffic read paths through targeted SQL and NoSQL query optimisation
- —Refactored high-traffic read paths with optimized indexing, query plans, and caching on SQL and NoSQL stores
- —Supported e-commerce scale with containerized services and AWS-backed deployment patterns
- —Led migration of legacy services to microservices using Docker and AWS for millions of users
- —Optimized CI/CD pipelines, reducing deployment cycles by 40% and enabling rapid feature releases
- —Integrated AI-driven solutions to enhance search relevancy and user engagement
- —Developed high-performance SPAs using React and TypeScript in a high-concurrency retail ecosystem
PythonNode.jsDockerAWSReactTypeScriptFastifyMongoDBLLMs
Commerce
Dukaan®
Backend Engineer
Bengaluru, India
May 2024 — Sep 2024
5 months
25%RAG response accuracy gain
99.9%Platform uptime
- —Optimized RAG pipelines with context-aware retrieval and evaluation frameworks
- —Integrated TypeSense and vector databases for 10,000+ daily inquiries with latency-focused tuning
- —Designed resilient backend architecture with seamless failovers during peak traffic
Node.jsExpress.jsPythonTypeSenseVector DBsPostgreSQLCohere
Internship
AI Planet
Python Developer
Mumbai, India
Feb 2024 — May 2024
4 months
- —Contributed to core architecture of an open-source agentic AI framework
- —Focused on multi-modal tool integrations and secure API orchestration
- —Engineered planning algorithms and memory-management systems for long-term context across multi-step workflows
PythonLangChainCrewAILLMsAPI Development
Internship
Fintricity
Data Engineering Intern
London, UK
Feb 2022 — Oct 2022
9 months
30%Client engagement lift
40%User engagement boost
- —Engineered data ingestion pipelines and graph data models in Neo4j for a flagship web application
- —Developed interactive data visualizations driving a 30% increase in client engagement
- —Spearheaded front-end development that boosted user engagement by 40% and cut onboarding time by 30%
Neo4jData IngestionGraph DatabasesUI/UXData Modeling