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✅ Solution Architect | Full-Stack | DevOps | Cloud | AI/ML | LLM Apps | IoT Hi, I’m Niladri — a Solution Architect and Full-Stack Developer with 15+ years of experience helping startups, SaaS companies, and enterprises design, build, automate, and scale secure, production-ready software systems. Clients hire me when they need more than a coder. They need someone who can understand the business goal, design the right architecture, build the product, automate infrastructure, integrate AI where it adds value, and keep the system scalable, maintainable, and cost-efficient. I can work as a senior engineer, architect, DevOps consultant, technical lead, or long-term technology partner. 📊 Skill Ratings DevOps & Cloud Architecture – ▓▓▓▓▓▓▓▓▓▒ 9.5/10 Solution Architecture – ▓▓▓▓▓▓▓▓▓▒ 9.5/10 Backend & API Engineering – ▓▓▓▓▓▓▓▓▓░ 9/10 AI/ML & LLM Integration – ▓▓▓▓▓▓▓▓░░ 8/10 IoT & Embedded Electronics – ▓▓▓▓▓▓▓▓░░ 8/10 Frontend Development – ▓▓▓▓▓▓▓░░░ 7/10 Mobile App Development – ▓▓▓▓▓▓▓░░░ 7/10 🚀 What I Can Help You With ☁️ Cloud, DevOps & Platform Engineering I design and deploy cloud-native infrastructure using AWS, Google Cloud, Azure, DigitalOcean, Heroku, and hybrid/on-premise systems. AWS: EC2, S3, RDS, Lambda, ECS, EKS, Fargate, DynamoDB, CloudFront, Route 53 GCP: Cloud Run, GKE, Firebase, Cloud SQL, BigQuery, Pub/Sub, AI APIs Azure: Functions, App Services, PostgreSQL, DevOps, cloud migration Core DevOps: Docker, Kubernetes, Helm, Terraform, CI/CD, GitHub Actions, GitLab, Jenkins, Bitbucket Pipelines, monitoring, backups, security hardening, high availability, and cost optimization. 🤖 AI/ML, LLM Apps & Automation I help businesses integrate AI into real products and workflows: LLM applications, OpenAI/AWS AI/Google AI integrations, RAG knowledge-base systems, AI chatbots, document processing, vector search with PostgreSQL/pgvector, recommendation engines, predictive analytics, and workflow automation. My focus is not just adding AI features — I design AI systems that are useful, secure, measurable, and practical. 💻 Full-Stack Web Development I build scalable web applications with clean architecture and maintainable code. Backend: Node.js, NestJS, Express, TypeScript, Python, Django, Flask, FastAPI, Java/Spring Boot Frontend: React.js, Next.js, Vue.js, Angular, admin dashboards, SaaS portals Databases: PostgreSQL, MySQL, MongoDB, Redis, DynamoDB, MariaDB, MS SQL I focus on API performance, database design, authentication, authorization, security, testing, and maintainability. 🔗 API Development & SaaS Integrations I build APIs, webhooks, integration layers, and event-driven systems. Experience includes Amazon MWS/SP API/Ads API, QuickBooks Online/Desktop, Xero, FreshBooks, HubSpot, Salesforce, Zoho, Zendesk, Stripe, Twilio, Slack, Asana, REST, GraphQL, Webhooks, Microservices, and Event-driven Architecture. 📱 Mobile App Development React Native, Flutter, and PWAs with real-time chat, push notifications, payments, GPS tracking, offline sync, dashboards, and cloud backend integration. 🌐 IoT & Embedded Systems Embedded Linux, Buildroot, Arduino, ESP, Raspberry Pi, RTOS, FPGA, Petalinux, RFSoC, ZCU111, XRF8, I2C, SPI, UART, TCP, MQTT, sensor integration, and firmware-to-cloud-to-dashboard platforms. 🧠 Technical Leadership I support teams with architecture, cloud review, code/PR review, CI/CD setup, security planning, database/API design, bottleneck resolution, team grooming, scalability planning, and engineering best practices. 🌟 Why Clients Hire Me ✔️ 15+ years of hands-on software, cloud, DevOps, AI, and IoT experience ✔️ Strong mix of architecture, development, automation, and technical leadership ✔️ Ability to work independently or lead a technical team ✔️ Experience with SaaS, fintech, e-commerce, AI, cloud, API integrations, and IoT systems ✔️ Practical mindset: I design systems that can be built, deployed, scaled, and supported ✔️ Strong focus on clean code, security, documentation, automation, and maintainability I don’t just deliver code — I help you build a reliable product, scalable platform, and stronger technical foundation. ⭐ Client Feedback “Nil headed up a full backend solution including RESTful API and AWS cloud setup. He is knowledgeable, understands your needs, and delivers creative, high-quality solutions.” — Douglas Stirling “Nil is an excellent developer — quick to grasp requirements, easy to communicate with, and always delivers well-tested, first-class work.” — Sat Sindhar “Niladri is a highly experienced full-stack programmer with thorough knowledge across technologies. I am extremely satisfied with his services.” — Vishal Agarwal “Niladri is the best at what he does. Very easy to communicate with, delivers flawless work, and provides great support after the job is done.” — Muzaffer Selimbeyoglu 📌 Background Degree in Computer Science CCNA | RHCE Diploma in Computer Hardware & Electronics GitHub Portfolio: fuzonmedia

I build full-stack products that grow with your business – from backend APIs to clean UIs and scalable AWS infrastructure. You get one senior engineer handling it all, so there are no handoff delays or coordination issues. I'm AWS Certified Developer and specialize in serverless systems, cost-effective cloud architecture, and CRM/SaaS platforms. My clients typically launch 30–40% faster and save $5K–15K/month on infrastructure. I solve complex problems with clean, production-ready solutions. No fluff, no delays – just results that scale.

Building an AI agent or RAG demo is easy. Making it reliable, secure, observable, and financially predictable in production is where most projects fail. I help SaaS and enterprise teams design, build, and rescue production AI systems on AWS. Expert-Vetted Top 1% AI Consultant on Upwork - 100% Job Success - $80K+ earned - 2,700+ hours delivered - 41 Upwork engagements - 9+ years of production engineering experience - Three AWS Professional certifications in Generative AI, Solutions Architecture, and DevOps ✓ CLIENTS USUALLY CONTACT ME WHEN - An AI agent works in a demo but fails with real users, tools, permissions, or business data - A RAG system retrieves the wrong information, produces weak citations, or becomes unreliable at scale - An AI proof of concept needs to become a secure and maintainable production product - Claude, OpenAI, or Amazon Bedrock must be connected to real business workflows - AWS infrastructure has reliability, security, scalability, or cost problems - A development team needs senior technical ownership rather than another task-based developer - An existing implementation needs architecture review, debugging, or production rescue → WHAT I BUILD PRODUCTION AI AGENTS - AI agents and agentic workflows - Claude, OpenAI, and Amazon Bedrock integrations - Tool calling, MCP servers, and external system integrations - Human approval and escalation workflows - Agent memory, state management, and context handling - Evaluations, guardrails, tracing, and failure recovery - Multi-agent orchestration where it is genuinely justified PRODUCTION RAG SYSTEMS - Document ingestion and processing pipelines - Vector search and hybrid retrieval - Metadata filtering, reranking, and access control - Reliable citations and source attribution - Retrieval and response evaluations - Enterprise knowledge assistants - Multi-tenant RAG architecture - OpenSearch and vector database integrations AWS ARCHITECTURE AND PLATFORM ENGINEERING - Serverless and event-driven systems - AWS Lambda, API Gateway, DynamoDB, SQS, EventBridge, and Step Functions - Terraform, AWS CDK, CloudFormation, and infrastructure automation - IAM, tenant isolation, security boundaries, and least-privilege access - Monitoring, observability, incident recovery, and architecture reviews - AWS cost optimization, performance improvement, and cloud migrations ★ SELECTED PRODUCTION EXPERIENCE - Worked on a high-volume ordering platform processing millions of transactions per month with strict uptime, performance, and recovery requirements - Delivered a 686-hour AWS engagement involving Cognito, Lambda, SQS, backend services, and production infrastructure, followed by a five-star client review - Improved production systems across SaaS, healthcare, fintech, cybersecurity, and streaming - Owned delivery across architecture, critical implementation, deployment, security, observability, and engineering handoff I work hands-on across Python, Node.js, TypeScript, APIs, distributed systems, cloud infrastructure, and modern AI frameworks such as LangGraph and LangChain. → HOW I WORK I do not begin by selecting an AI framework. I begin with: - The business workflow - The users and permission boundaries - The available data - The expected result - The failure modes - The security requirements - The operating cost - The team's ability to maintain the system From there, I design the smallest architecture that can safely achieve the required outcome. I will also tell you when: - An AI agent should be a deterministic workflow - RAG is unnecessary for the use case - A managed service is creating avoidable cost or lock-in - The proposed architecture is too complex - A feature is likely to waste more money than it creates in value - A prototype is not yet ready for production use Avoiding the wrong architecture often saves more time and money than writing additional code later. You can expect clear communication, visible progress, documented decisions, honest risk analysis, and production-focused validation. I stay involved through production readiness and engineering handoff, not only prototype delivery. I am a strong fit when AI must interact with real users, business data, external tools, and production infrastructure. Send me your architecture, requirements, repository context, or production problem. I will review the context, identify the highest-risk area, and recommend the most practical starting point.

I help engineering teams and technical founders make the right system decisions before they become expensive — scoping what to build, de-risking architecture before irreversible choices are made, and owning delivery through to scale. My background spans cloud architecture, solution architecture, and database systems across AWS and Azure. The combination matters: most production failures I have seen trace back not to bad code, but to structural decisions made early in the schema, the system boundaries, or the deployment model — that compounded quietly until they could not be undone. I am based in Armenia and work async-first with clients across the US, Europe, and Australia. Architecture work — system design, technical reviews, decision documentation, governance frameworks — does not require timezone overlap. My clients do not experience geographic friction. 🔹 𝐓𝐡𝐫𝐞𝐞 𝐫𝐞𝐜𝐞𝐧𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐭𝐡𝐚𝐭 𝐜𝐚𝐩𝐭𝐮𝐫𝐞 𝐡𝐨𝐰 𝐈 𝐰𝐨𝐫𝐤: 𝐆𝐃𝐂 𝐌𝐞𝐝𝐢𝐚 (𝐈𝐫𝐞𝐥𝐚𝐧𝐝) — built an LLM-assisted database audit engine running across 3 MySQL clusters and 15 production nodes. 13 independent checkers feed findings to the LLM, which grades each as Critical / Major / Minor / Trivial and writes a short, grounded explanation. Runs hands-off 365 times a year. 𝐇𝐑𝐒 𝐆𝐫𝐨𝐮𝐩 (𝐂𝐨𝐥𝐨𝐠𝐧𝐞, 𝐆𝐞𝐫𝐦𝐚𝐧𝐲) — designed and built financial data pipelines on AWS that bridge MS Navision (ERP) and SAP through a single canonical model. Safe to replay, with scheduled reconciliation. 𝐆𝐥𝐚𝐬𝐬𝐰𝐚𝐥𝐥 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 (𝐔𝐊) — Cloud Engineer on the Content Disarm and Reconstruction platform now trusted by NATO and U.S. and U.K. national security agencies. Helped adapt the platform for AWS EKS, Azure AKS, and K3s, and built the file ingress orchestration plugin handling terabytes of potentially infected files. 🧭 𝐇𝐨𝐰 𝐈 𝐰𝐨𝐫𝐤 I don't approach projects as feature delivery. I approach them as temporary or ongoing technical ownership — short engagements that clarify direction, longer ones that carry the system through to scale. The shape is the same in both: • Reduce MVP scope while keeping the core value loop intact • Define cloud architecture and system constraints before implementation begins • Make decisions explicit instead of accumulating quiet assumptions • Separate short-term delivery from long-term structural risk • Hand off to in-house engineers cleanly when the moment is right Some engagements take two weeks. Some turn into multi-year work. The goal in both is the same — systems that don't need heroics to keep running. 🎯 𝐖𝐡𝐞𝐫𝐞 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐮𝐬𝐮𝐚𝐥𝐥𝐲 𝐠𝐞𝐭 𝐬𝐭𝐮𝐜𝐤 In early- and growth-stage systems, the biggest problems are rarely about tooling or raw engineering skill. They are decision gaps: • Feature lists that grow faster than clarity • AI is treated as a black box instead of a constrained system • Developers hired before the success criteria are defined • Architectural decisions deferred until they're expensive to reverse • "We'll fix it later" choices that quietly become permanent That's the layer I focus on stabilizing first — so execution stays fast without becoming brittle. ⛁ 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 & 𝐝𝐢𝐚𝐠𝐧𝐨𝐬𝐭𝐢𝐜𝐬 Production databases are where architectural decisions surface most visibly — slow queries, bloated indexes, configuration drift, schema choices that worked at 10K rows and break at 10M. I have extensive hands-on experience with PostgreSQL, MySQL, and MariaDB in high-load production environments. For teams that need a fast, structured assessment: I offer a fixed-price SQL database audit via my Project Catalog — a prioritized diagnostic report delivered in 1–2 days, ranked by business impact. 🧱 𝐒𝐭𝐚𝐜𝐤 • Databases — PostgreSQL, MySQL, MariaDB, OpenSearch, Elasticsearch, DynamoDB • Cloud — AWS, Azure, Kubernetes, Docker, serverless • Security — IAM, encryption, access boundaries, secure data flows • DevOps — CI/CD, GitHub actions, CloudFormation, observability • AI-adjacent — guardrails, confidence gating, deterministic vs. generative boundaries Technology serves decisions, not the other way around. 📅 𝐄𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐟𝐨𝐫𝐦𝐚𝐭𝐬 • Long-term architecture and delivery ownership • Fractional CTO or technical advisor • Short-term advisory (1–4 weeks) • Fixed-price SQL database audit (Project Catalog — from $750) Most successful collaborations start small and grow naturally once alignment is in place. 📨 𝐋𝐞𝐭'𝐬 𝐭𝐚𝐥𝐤 If you are unsure what to build, what to cut, or how to de-risk a critical phase — or if your database is showing signs of trouble — a short conversation usually makes sense. From there, we decide together on the right shape of engagement.

Hi, I’m Mehul, a Top-Rated-Plus AWS Expert and DevOps Engineer who helps startups and founders launch and scale reliable SaaS, healthcare, and fintech platforms on AWS. ✅ Top 1% Upwork Freelancer ✅ 125+ Projects Completed ✅ 7000+ Hours Worked ✅ Top-Rated Plus on Upwork ✅ AWS Certified Developer - Associate 🏆 🏆 I’ve designed systems serving 2M+ users, built HIPAA-compliant healthcare apps, and helped teams cut cloud bills by 30–40 % without compromising performance. My focus is simple: build it once, make it scale, and keep your costs under control. ✅ What I Do ➥ Architect secure, serverless AWS setups using Lambda, API Gateway, and DynamoDB ➥ Deploy AI Agent to AWS with Bedrock ➥ Automate deployments with Terraform, GitHub Actions, and CodePipeline ➥ Optimise infrastructure for speed, uptime, and cost 💡 Why Work With Me ➥ 7+ years in AWS DevOps ➥ $300 K+ earned on Upwork, 100 % Job Success Known for clear communication, quick delivery, and long-term reliability Let’s connect if you’re building a product and want an AWS setup that’s secure, scalable, and easy to manage so you can focus on growing your business while I handle the cloud. Experienced with Amazon EC2, S3, RDS, Aurora, DynamoDB, ElastiCache, CloudFront, API Gateway, Step Functions, EKS, Fargate, CodePipeline, CodeBuild, CloudWatch, Grafana, Prometheus, GuardDuty, Security Hub, AWS Organisations, SCPs, KMS, Secrets Manager, IAM, WAF, Route53, ACM, Amplify, SageMaker, Bedrock, OpenSearch, and CloudFormation. Python, Bash, TypeScript, Node.js, Docker, Kubernetes, GitHub Actions, GitLab CI, Jenkins, n8n, Zapier.

Building something complex? I help companies architect, build, and scale systems that actually work — from first commit to 1M users. And I can prove exactly how I do it. Why Clients Hire Me After 74+ Upwork contracts and $200K+ delivered, I've learned that most projects fail for the same reasons: unclear scope, wrong architecture decisions early on, and vendors who say "yes" to everything. I do the opposite — I ask hard questions upfront so we don't discover problems in production. How I Work: AI-Augmented Development I don't just use AI tools — I've systemized them into a Multi-Agent Development Methodology: → Every decision documented and versioned (no tribal knowledge) → Full audit trail — see exactly how your project evolves → Real-time visibility into progress (not just status updates) → Clean handoffs — the next developer won't curse me What I Do → AWS Architecture & Infrastructure — Design, migration, optimization, security → Full-Stack Development — React, Angular, Node.js, Python, Java → Compliance Systems — HIPAA, SOC2, enterprise-grade security → IoT & Real-Time Data — AWS IoT Core, sensor networks, dashboards → Trading & Financial Systems — TradingView, Pine Script, algorithmic strategies Where I Add Most Value → Projects where "getting it right" matters more than "getting it cheap" → Systems that need to scale, comply, or integrate with complex infrastructure → Teams that want a technical partner, not just a code vendor → Rescuing projects that previous developers made a mess of → Teams who value documentation and full visibility The Numbers → 100% Job Success Score → Expert-Vetted status (top 1% of Upwork talent) → $200K+ earned on platform → 50+ developers in my agency for larger engagements → 22+ years building enterprise systems (Hewitt, Xerox, Cognizant) Certifications → AWS Solutions Architect – Professional → AWS Advanced Networking – Specialty → AWS Security, Cloud Economics, and Technical Professional Industries I've Built For Healthcare (HIPAA) · Fintech · SaaS · IoT · Insurance · Logistics · Manufacturing · Legal Tech How to Start Send me a message with: → What you're trying to build or fix → Your timeline → Any constraints I should know about I'll give you an honest assessment — including whether I'm the right fit.