AI Architect
Building scalable, production-ready AI solutions end-to-end — from LLM applications and multi-agent systems to data platforms and intelligent workflows that deliver measurable business impact.
About Me
I am a results-driven AI and Cloud professional with a strong track record of designing, building, and scaling intelligent systems that deliver measurable business value. I specialize in transforming complex data into actionable insights and production-ready solutions.
My expertise spans end-to-end AI lifecycle development — from data engineering and model design to deployment and optimization within cloud-native environments. I enable organizations to move from experimentation to robust, enterprise-grade AI solutions.
What differentiates me is not only technical depth but also a strategic mindset. I approach every project with a focus on impact, efficiency, and innovation — aligning technology with business goals and driving continuous improvement.
I am known for being proactive, detail-oriented, and highly adaptable. Whether collaborating with cross-functional stakeholders or leading technical initiatives, I communicate clearly and execute with precision to deliver scalable, sustainable solutions.
Technical Toolkit
Full-stack AI Architecting from data ingestion to production deployment.
Portfolio
Real-world AI systems designed, built, and deployed from scratch.
Built a production-ready AI testing assistant with a 5-tool pipeline that autonomously generates comprehensive test cases, performs root cause bug analysis, and produces structured QA plans via Claude Sonnet. Implemented a secure FastAPI backend proxy with encrypted API key management, deployed on Railway with a multi-page interactive frontend serving Test Generator, Bug Analyzer, QA Planner, Onboarding Assistant, and Analytics modules. Integrated CI/CD hooks for GitHub, AWS DevOps, and Jenkins with auto-deploy on every commit.
Built a full-stack AI compensation analytics platform with a 7-module architecture covering market benchmarking against P25–P90 percentiles, gender pay gap analysis with statistical significance testing, merit matrix simulation, STI payout modelling, and promotion cost planning across 500 synthetic employees in 5 countries, powered by a GPT-4o AI Agent with function calling for natural-language querying of live compensation data.
Built a production-ready 4-agent AI pipeline that classifies client inquiries, performs real-time web research, generates personalised multi-language replies via Claude Opus, and autonomously routes outputs to Slack with PDF proposals. Integrated Zapier automation for 24/7 email processing, deployed on Railway with a live analytics dashboard tracking ROI across 7 languages.
Built a RAG-based AI exam tutor using LangChain and OpenAI GPT-4 with Pinecone for semantic search. Multi-source ingestion (YouTube + PDFs), custom mock exam & grading tools, deployed on Hugging Face Spaces. Evaluated via LangSmith.
Designed, trained, and deployed a CNN achieving ~90% validation accuracy on CIFAR-10. Applied data augmentation, precision-recall evaluation, confusion matrices, and iterative hyperparameter tuning.
Implemented a robust CI/CD pipeline using AWS CodeCommit, CodeBuild, and CodeDeploy. Deployed Node.js on EC2 via Elastic Beanstalk with automated build, test, and deployment workflows.
Designed and automated AWS infrastructure using Python and Boto3 SDK. Implemented DevOps practices for provisioning, monitoring, and scaling cloud resources with CI/CD workflows for infrastructure as code.
Collected social media data via cloud computing infrastructure, analyzed big data, and extracted sentiment insights from posts. Early project bridging cloud data engineering with NLP analysis.
Career
From cloud operations and data engineering to AI systems engineering.
Academic Background
Credentials
Verified expertise across AI, cloud platforms, and data engineering.
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