Professional Overview
I’m a Technical Lead and AI-augmented Full Stack Developer with 10+ years of professional experience architecting, developing, and deploying modern web and cloud applications. I specialize in delivering end-to-end software solutions built on Microsoft technologies — now supercharged with AI development tools like ChatGPT, Claude, bolt.new, and Serena to drive faster delivery, better quality, and more intelligent automation.I've led teams, scaled enterprise systems, migrated legacy apps to cloud platforms, and consistently delivered high-performance products across diverse industries, including finance, healthcare, retail, and tech.🧠 Core Competencies: Backend: C#, .NET Core, ASP.NET MVC, Web API, MVVM, Entity Framework, LINQ, SQL Server Frontend: Angular (2–18), AngularJS, React.js, Node.js, HTML5, CSS3, Bootstrap, Tailwind, Sass Cloud & DevOps: Azure (App Services, Functions, DevOps), AWS (Lambda, EC2, S3), Docker, CI/CD Pipelines AI Tools: ChatGPT, Claude, bolt.new, Serena (for coding, testing, documentation, automation) APIs & Integration: REST, SOAP, XML, XSLT, WSDL, Stripe, PayPal, SagePay, Amadeus, LinkedIn, Expedia Database Tech: SQL Server, MongoDB, MySQL, PostgreSQL UI & Reporting: Telerik, DevExpress, Power BI Version Control & Collaboration: Git, Azure DevOps, TFS, SVN, Jira, Trello, Asana🔥 What Sets Me Apart:✔️ Proven leadership as a Tech Lead, mentoring teams and delivering client success✔️ Strong experience in cloud-native architectures and AI-enhanced workflows✔️ Deep full-stack expertise combined with excellent business communication skills✔️ Agile, adaptable, and continuously learning to stay ahead of the curveLet’s connect and build intelligent, scalable, and high-performance solutions that move your business forward — powered by code, cloud, and AI.
Areas of Expertise
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
