Applied AI Engineer · The Cloud Intelligence Inc. Apr 2026 – Present | Remote, India

• Designed and developed a proof-of-concept conversational Shopping AI Assistant for SMSA Express — Saudi Arabia's leading courier and logistics conglomerate (230+ countries, 3,000+ couriers) — enabling end-users to query shipment status, explore services, and initiate delivery workflows through a natural language interface integrated with SMSA's existing APIs.
• Led AI feature development for miDoc, TCI's flagship AI-powered healthcare platform, engineering miDoc Cortex — a multi-turn conversational agent that allows patients and doctors to perform any action available in the miDoc UI (updating doctor notes, logging patient profiles, surfacing health trends) entirely through natural language conversation.
• Architected miDoc Cortex as a full agentic system with MCP (Model Context Protocol) server integration, exposing all miDoc platform APIs as structured tools; the agent resolves user intents, selects the appropriate tool, and confirms actions before execution — enabling safe, human-in-the-loop automation of healthcare workflows.
• Implemented agent orchestration layer coordinating multi-step reasoning, intent disambiguation, and tool chaining across miDoc's full API surface — covering patient profile management, consultation note updates, appointment context enrichment, and medication retrieval through GenAI-backed knowledge bases.
• Conduct hands-on AI training sessions for TCI's AI Practitioner Programme — an 8-week, developer-focused programme that takes engineers from concept to a deployable production-grade AI agent; sessions emphasise real enterprise codebases, live architecture walkthroughs, and practical agent-building over theory.
• Serve as dedicated instructor and technical mentor, guiding trainees through real TCI production systems, conducting daily follow-ups and code reviews, and supporting participants end-to-end in scoping, designing, and shipping custom AI agents.

Tech Stack: Python, FastAPI, Node.js, TypeScript, LangChain, LangGraph, MCP, CrewAI, RAG Pipelines, Vector Search, OpenAI / Anthropic APIs, PostgreSQL, REST API Design

Full Stack Developer · Finanshels Feb 2025 – Apr 2026 | Remote, India

• Spearheaded development of a comprehensive Practice Management platform (Next.js + NestJS) automating full-cycle organisational workflows — bridging sales pipelines, project management, and accounting systems — with PostgreSQL schemas and DynamoDB Streams optimised for high-throughput billing workflows.
• Architected a production LLM-powered AI Bookkeeper using a custom multi-agent orchestrator (CrewAI + LangChain); designed LLM-ready APIs and RAG pipelines with vector retrieval, reducing bookkeeping TAT by over 90% (weeks to under one day).
• Implemented end-to-end LLM evaluation pipelines tracking retrieval precision, tool-calling accuracy, and hallucination rates in live environments using Pytest — enabling continuous quality improvement on AI workflows.
• Built and deployed a secure, centralised client portal integrating unified client profiles, timesheet tracking, task management, and automated report delivery — significantly improving operational visibility and client support delivery.
• Built third-party integrations with accounting platforms, CRMs, and billing systems — designing normalised data pipelines and webhook-driven sync layers to keep interconnected systems in real-time consistency.
• Designed event-driven microservices on AWS (Lambda, DynamoDB Streams, SQS) ensuring fault tolerance, high availability, and low-latency state propagation across interconnected financial data pipelines.
• Integrated MCP (Model Context Protocol) servers for secure, standardised tool access across agent workflows — enabling scalable inter-agent communication and external API orchestration.
• Directed engineering operations in the absence of the VP of Engineering — managed CI/CD deployment pipelines, led daily stand-ups, and drove technical decision-making during high-level strategic planning.
• Led incident management, root cause analysis, and observability setup; championed API-first, LLM-ready design principles and mentored junior engineers through code reviews and design discussions.
• Authored and maintained comprehensive Swagger / OpenAPI documentation across all platform APIs; implemented OAuth2 / JWT authentication flows for secure client portal and third-party integration access.

Tech Stack: Python, Next.js, NestJS, TypeScript, React, Tailwind, PostgreSQL, DynamoDB, AWS (Lambda, SQS, S3), Azure DevOps, CrewAI, LangChain, LangGraph, Docker, Redis, pgvector, Pytest, Swagger/OpenAPI, OAuth2/JWT

Python Developer (Backend) · The Good Glamm Group May 2024 – Feb 2025 | Mumbai, India

• Migrated legacy monoliths to event-driven microservices on Docker/AWS; designed async SQS/SNS pipelines for real-time inventory and order state propagation serving millions of concurrent users.
• Built and optimised FastAPI / Fastify / Flask backend services using BFF (Backend for Frontend) pattern to decouple UI and backend logic; improved p99 latency by 35% on high-traffic read paths through targeted SQL and NoSQL query optimisation (PostgreSQL, MongoDB).
• Integrated AI-driven semantic search using embeddings and vector retrieval to boost product discovery relevance; improved recommendation quality measurably via A/B testing.
• Streamlined CI/CD pipelines (GitHub Actions) reducing release cycles by 40%, enabling safe, rapid feature rollouts with automated test coverage gates.

Tech Stack: Python, FastAPI, Flask, Node.js (Fastify), MongoDB, PostgreSQL, Redis, AWS (SQS/SNS, EC2), Azure DevOps, Docker, LLM APIs

loopvoice.ai — AI-Powered Voice Automation Platform for Shopify | Live Product | Built in 1.5 months

• Built and shipped a fully live AI voice automation platform for Shopify stores in 1.5 months using AI-assisted tooling (Cursor, Claude Code) — integrating voice AI APIs (STT/TTS) to automate abandoned cart recovery, order follow-ups, and customer outreach via automated voice calls, email, and SMS.
• Designed a DAG-based visual flow builder — modelled flows as Directed Acyclic Graphs (DAGs) to enable merchants to create event-triggered automation (abandoned checkout, order placed, etc.) with configurable wait nodes and branching logic — integrated Redis-based job scheduling for reliable timed execution.
• Built custom AI voice agents with RAG-powered knowledge bases (ingesting store websites and policies) to handle real customer queries — and a campaign feature for batch-calling segmented customer lists with configurable call frequency and rate controls.
• Integrated Telnyx for in-platform phone number provisioning across global regions; full-stack built on Next.js, PostgreSQL, GCP, and Redis.

Next.js, PostgreSQL, GCP, Redis

bot9.ai — Enterprise Customer Support Chatbot Platform | Used by RentoMojo PAN India

• Built a production-grade enterprise chatbot platform currently deployed for RentoMojo across India — supports configurable bot logic, team member management, and omnichannel integrations (Slack, Discord, Freshchat, WhatsApp).
• Enabled direct API integration with enterprise production databases — allowing the bot to act on live data (orders, rentals, accounts) rather than static knowledge; powered by Typesense (vector search) for semantic retrieval and built on Node.js, React, and PostgreSQL.

Node.js, React, PostgreSQL

OpenAGI — Open-Source Autonomous Agent Framework | Feb 2024

• Built core backend infrastructure for an open-source autonomous agent framework; implemented MCP servers enabling secure, scalable tool integration and inter-agent communication across distributed workflows.
• Engineered custom planning algorithms, memory-augmented state machines, and self-correcting execution pipelines with fault recovery — applied Control Plane architecture to enable long-running agentic workflows.

LegalEase — Compliance & Document Automation Platform for MSMEs | Nov 2023

• Designed a scalable FastAPI backend with automated OCR ingestion pipelines, RESTful microservices, and semantic document retrieval using vector embeddings and pgvector.
• Implemented secure data storage and retrieval with AWS S3 and IAM role-based access controls, ensuring enterprise-grade data privacy and encryption compliance.