Freelancers using AWS in JaipurFreelancers using AWS in Jaipur
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Abhishek Anand's avatar
Abhishek Anand
Jaipur, India
Full-stack developer building MVPs, marketplaces and CRMs.
New to Contra
Full-stack developer building MVPs, marketplaces and CRMs.
Cover image for Title: KYAT Gold — Digital
Title: KYAT Gold — Digital Gold Savings & Chit Fund Platform Description: A production fintech platform for a gold trading business, built end to end — customer mobile apps plus the admin console that runs the operation behind them. The product covers three revenue lines that most gold businesses run separately. Customers buy digital gold and silver as a SIP at live MCX rates, with holdings kept in a vault ledger. They join traditional chit groups with monthly installment collection and scheduled draws. And branch staff can transact over the counter on a customer's behalf through an OTC desk, with custom price override for negotiated rates. The admin console is where the real complexity sits. Operators get one view of daily collections, overdue exposure, autopay success rate and payout queue, alongside time-series collection analytics and per-group draw progress. Because these are savings schemes members have to trust, monthly winner selection runs on SHA-256 seed verification with a downloadable audit trail — the draw is provably fair rather than something the operator can quietly influence. The hardest part wasn't any single screen. It was reconciliation: gold prices move continuously, chit installments arrive irregularly, payouts are scheduled monthly, and every one of those has to stay consistent against a vault ledger that regulators and members can both audit. Getting that right shaped most of the backend design. Mobile apps in Flutter for iOS and Android, PayU handling payment collection, and a Node.js backend managing ledgers, vault accounting, autopay retries and scheduled payouts.
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Cover image for Title: Enterprise ATS & Hiring
Title: Enterprise ATS & Hiring Requisition Platform Description: An applicant tracking system built for enterprise recruitment teams who had hiring data scattered across spreadsheets, inboxes and three different tools — with no single view of what was actually happening. The core of it is the admin dashboard: a company-wide pipeline funnel from application through screening, interview, offer and hire, with velocity metrics on each stage so leadership can see where candidates stall rather than just how many are in the system. Alongside it sits recruiter performance comparison, job health monitoring and a hiring calendar. Beyond the dashboard, the platform handles resume parsing and candidate search, job posting and interview scheduling, client and vendor management, and invoicing. I built an asynchronous Gmail and Outlook inbox sync on AWS SQS with a dedicated worker process, so recruiter email threads attach to the right candidate record automatically instead of being copy-pasted in. The piece I'm proudest of is the hiring requisition module. An employee raises a hiring request, it routes up the reporting hierarchy for approval, branches depending on whether the role is budgeted or unbudgeted, and on final sign-off creates the job in the ATS automatically for HR to hire against. It's designed for roughly 600-person org hierarchies, which meant getting the approval routing right mattered more than any individual feature. Stack: React · Node.js · Express · MongoDB · AWS SQS · Gmail & Outlook OAuth Skills to tag: Full-Stack Development, React, Node.js, MongoDB, API Integration, SaaS, Dashboard Design, AWS
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Cover image for Title: KYAT Gold — Gold
Title: KYAT Gold — Gold Savings App (iOS & Android) Description: The customer side of a digital gold savings platform, built in Flutter for iOS and Android. The app does three things people usually have to visit a jeweller for. It runs digital gold and silver SIPs at live market rates, with holdings tracked to three decimal places in a personal vault. It lets customers join monthly savings groups — the traditional chit model — and see exactly how full a group is, how many tokens remain, and when their next installment is due. And it handles the payments for both, with a countdown to the due date and one-tap settlement. The screen I'd point to is the scheme calculator. Gold savings groups are genuinely hard to understand — there's a monthly amount, a token count, a total commitment, a guaranteed floor and a variable upside, and most people encounter all of that for the first time at the moment they're deciding whether to trust you with money for eleven months. So it's built as something you drag rather than read: move the token slider and total investment, minimum guaranteed return and maximum return all update together. The maths was never the difficult part. Making the commitment legible before someone signs up was. The vault handles a related problem in the other direction. Gold is priced per gram, but people think in rupees, so buying works either way with a unit switch — enter ₹500 or enter 0.5g and the app resolves it against the live rate. Onboarding is phone number and OTP only. No password, no email, no form. For a first-time gold saver the signup screen is where you lose them. Flutter and Dart on the client, Node.js and MongoDB behind it, PayU for collection, and a live pricing feed driving every rate shown in the app.
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Cover image for Title: Cognitome — Gamified Cognitive
Title: Cognitome — Gamified Cognitive Assessment Platform Description: A web platform that delivers validated psychology experiments as playable browser tests, built for a research and assessment client based in Dubai. It implements eight standard cognitive paradigms — Stroop, Numerical Stroop, Flanker, Corsi Block, Attentional Blink, the Attention Network Test, the Implicit Association Test, and the Wisconsin Card Sorting Task. Each one runs as a guided flow: instructions, a worked demo, a practice round, then the timed run, ending in a results breakdown. Every trial produces a metrics record, and effect scores are computed from those rather than from summary averages, so the output is analysable rather than just a number on a screen. Administrators pick which experiments a participant should take, set an expiry, and the system generates an access-coded link. Participants open the link and begin — no account, no signup — and results are captured and stored on completion. That mattered because research participants abandon anything that asks them to register before they've seen the task. The genuinely hard part was timing. These paradigms measure differences in reaction time that are often only tens of milliseconds wide, and a browser is a hostile environment for that — variable frame rates, input latency, background tab throttling. Getting stimulus presentation and response capture accurate enough for the effect sizes to mean anything drove most of the frontend architecture. Any of these tests is easy to build badly and the result looks identical until you check whether the numbers replicate known findings. React 19 with Vite and Tailwind on the frontend, Node.js and MongoDB behind it for session generation, access control and result storage.
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AWS(2)
Disha Chopra's avatar
Disha Chopra
Jaipur, India
Full-Stack Developer building AI Agents & RAG Systems
New to Contra
Full-Stack Developer building AI Agents & RAG Systems
Cover image for RepoSphere - GitHub-Inspired Version Control
RepoSphere - GitHub-Inspired Version Control Platform Full-stack, GitHub-inspired platform with JWT authentication, repository management, issue tracking, and real-time search. Built a RESTful API with user dashboards, and reduced code redundancy by 35% through modular architecture. Deployed on AWS Amplify.
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Cover image for FinSense - AI-Powered NPA Prevention
FinSense - AI-Powered NPA Prevention Platform for Banking AI-powered, post-disbursement loan health monitoring system built for SBI-scale banking use cases. Continuously monitors borrower financial behavior after loan disbursement, scores risk on a 0–100 scale across 4 tiers using XGBoost with SHAP-based explainability, and deploys a conversational AI agent to proactively engage at-risk borrowers 60–90 days before default — instead of only scoring creditworthiness at application time like traditional systems. Built the FastAPI backend (loan, risk, agent, and dashboard routers), automated risk re-scoring via Celery + Redis, and real-time dashboard updates via WebSockets, with a React + Tailwind frontend for officer-facing risk visualization.
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Cover image for SENTINEL - Edge AI Driver
SENTINEL - Edge AI Driver Assistance System Backend Lead for an edge AI ADAS (driver assistance) system built for Indian road conditions. Multi-stage ML pipeline covering sensor fusion, scene classification, risk scoring, GradCAM/XAI explainability, and federated learning. Built the backend and deployment pipeline, integrating ONNX and PyTorch runtimes to serve model inference in production.
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Cover image for Financial Decision Intelligence Platform —
Financial Decision Intelligence Platform — Multi-Agent Risk Analysis Multi-agent platform (LangGraph) that ingests SEC 10-K filings via XBRL extraction, runs Altman Z-Score and Piotroski F-Score risk models, and generates investment committee reports. Pipeline includes RAG-based risk retrieval (FAISS + Sentence Transformers), XGBoost ML inference, and Gemini API report generation — served through a FastAPI backend with /analyze, /compare, and /report endpoints for multi-company investment ranking. Stack: Python, LangChain, LangGraph, FAISS, XGBoost, FastAPI
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AWS(1)
Rupesh Saini's avatar
Rupesh Saini
Jaipur, India
DevOps & Automation Engineer | RedHat Certified
DevOps & Automation Engineer | RedHat Certified
Cover image for Website Migration to AWS Cloud
Website Migration to AWS Cloud
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Cover image for WebApp Deployment on Kubernetes
WebApp Deployment on Kubernetes
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Cover image for Automated Signaling Firewall Deployment using Ansible
Automated Signaling Firewall Deployment using Ansible
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AWS(1)
Rajesh Verma's avatar
Rajesh Verma
Jaipur, India
Expert Data Architect for Cloud & Big Data Solutions
Expert Data Architect for Cloud & Big Data Solutions
Cover image for Optimizing ETL Pipelines for Real-Time Data Streaming
Optimizing ETL Pipelines for Real-Time Data Streaming
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Cover image for EverBuild, SOQ & Radine Migration,DSS DataLake, CD Capabilities
EverBuild, SOQ & Radine Migration,DSS DataLake, CD Capabilities
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Cover image for Implementing Big Data Solutions on Cloud Platforms
Implementing Big Data Solutions on Cloud Platforms
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AWS(3)