TK.

Chapter 02

Experience

Career timeline from resume — fintech, e-commerce, commerce backends, agentic AI, and data engineering (Feb 2022 — present).

Applied AI

The Cloud Intelligence Inc.

Applied AI Engineer

Remote, India

Apr 2026 — Present

Present

MCPFull agentic healthcare platform
8-wkAI Practitioner Programme
  • —Designed and developed a conversational Shopping AI Assistant for SMSA Express — Saudi Arabia's leading courier and logistics conglomerate (230+ countries, 3,000+ couriers) — enabling natural language queries for shipment status, service discovery, and delivery workflow initiation via SMSA APIs.
  • —Led AI feature development for miDoc, TCI's flagship AI-powered healthcare platform, engineering miDoc Cortex — a multi-turn conversational agent enabling patients and doctors to perform any miDoc UI action through natural language.
  • —Architected miDoc Cortex as a full agentic system with MCP (Model Context Protocol) server integration, exposing all miDoc platform APIs as structured tools; agent resolves user intents, selects the appropriate tool, and confirms actions before execution for safe human-in-the-loop automation.
  • —Implemented agent orchestration layer for multi-step reasoning, intent disambiguation, and tool chaining across miDoc's full API surface — patient profiles, consultation notes, appointments, and medication retrieval via GenAI-backed knowledge bases.
  • —Conduct hands-on AI training sessions for TCI's AI Practitioner Programme — an 8-week developer-focused programme guiding engineers from concept to a deployable, production-grade AI agent with real enterprise codebases.
  • —Serve as dedicated instructor and technical mentor, guiding trainees through real TCI production systems, daily code reviews, and end-to-end agent scoping, design, and delivery.
PythonFastAPINode.jsTypeScriptLangChainLangGraphMCPCrewAIRAG PipelinesVector SearchOpenAI / Anthropic APIsPostgreSQL
Fintech

Finanshels

Full Stack Developer

Remote, India

Feb 2025 — Apr 2026

14 months

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