Banketeshvar Narayan
Software Engineer · Full Stack Developer · AI & Agentic AI Practitioner
Software engineer with 15+ years of experience in enterprise full stack development, Microsoft technologies, banking and financial systems, DevOps modernization, and AI-assisted software engineering. I connect long-term engineering depth with modern AI practices to help teams build better, faster, and more confidently.
Professional Journey
My engineering career started in the early 2010s, building data-intensive applications on the Microsoft stack. Over the years I moved across full stack web development, enterprise system integration, cloud migration, DevOps modernisation, and most recently into AI-assisted engineering.
A significant part of my experience sits in banking and financial technology — working on large-scale, high-availability platforms where correctness, traceability, and regulatory alignment matter. That grounding shapes how I think about software quality, observability, and change management.
Along the way I was recognised as a Microsoft MVP in 2016 and as a four-time C# Corner MVP for contributions to the developer community through technical writing, talks, and knowledge sharing — something that remains a consistent thread throughout my career.
What I Do
Full Stack Engineering
- C# · .NET / .NET Framework · ASP.NET Core
- Angular · TypeScript · JavaScript
- SQL Server · Database Design & Optimisation
- Microservices · Micro-Frontend Architecture
- REST APIs · Event-Driven Systems
Cloud & DevOps
- Microsoft Azure · Cloud Architecture (AZ-900)
- Azure DevOps · CI/CD Pipelines
- GitLab · GitLab CI/CD
- Docker · Kubernetes · Ansible
- Infrastructure as Code · Environment Automation
Enterprise Modernisation
- Legacy platform refactoring and migration
- Monolith-to-microservices decomposition
- SCM migration (GitLab, GitHub, Azure DevOps)
- Test automation and quality engineering
- Cross-team technical enablement
AI-Assisted Engineering
- Agentic AI design and MCP-based workflows
- RAG pipelines · LangChain · LangGraph
- AI-assisted code review and developer tooling
- GitHub Copilot · GitLab Duo · Kiro
- Prompt engineering and reusable AI skills
Current Focus
Right now I'm deep in the intersection of enterprise software engineering and agentic AI. That means less about replacing developers with AI, and more about building the tooling, workflows, and conventions that let engineering teams use AI thoughtfully and effectively.
AI Coding Tools
- GitHub Copilot
- GitLab Duo
- Amazon Kiro
- Roo Code / Codex
Agentic AI / LLM
- MCP-based workflows
- LangGraph multi-agent
- RAG · AutoGen
- Prompt Engineering
Learning & Writing
- AI-102 preparation
- GitHub Copilot cert
- Agentic AI patterns book
- Technical blog series
Engineering Philosophy
Understand the problem before reaching for the solution. A large part of software quality comes from clarity — clear requirements, clear data models, clear contracts between services. I've learned that slowing down at the beginning usually speeds things up at the end.
Make the invisible visible. Good observability, meaningful logging, and traceable deployments are not optional extras — they are part of the software. In regulated environments where I've worked, this isn't just best practice; it's essential.
Automate what costs you time repeatedly. Whether it's CI/CD pipelines, environment provisioning, code review checklists, or now AI-assisted code generation — automation done well returns time and reduces human error.
Share what you know. Writing, talking, and open-source contribution are how individual learning compounds into team capability. I've published 25+ technical articles, spoken at community events, and continue to invest in knowledge transfer as a core professional habit.
Community & Knowledge Sharing
C# Corner
Technical articles, tutorials, and community contributions on Microsoft technologies. Recognised as MVP four times.
View articles →BankyBluePrints
AI-focused technical articles, Agentic AI notes, and developer productivity guides.
Visit site →Stack Overflow
Q&A and technical participation across developer topics since 2011.
Open profile →Who I Am as an Engineer
I identify as a practitioner first — someone who builds things, breaks things, and learns in public. I'm comfortable working across the full stack and across the full delivery cycle, from requirements and architecture through to deployment and observability.
I've worked in teams ranging from small start-up style squads to large enterprise programmes. What I value most is clarity of purpose, technical honesty, and a culture where learning is treated as part of the job — not a luxury.
The shift to AI-assisted engineering is the most interesting moment in software development I've seen in 15 years. I'm actively working out what it means to be a thoughtful, senior engineer in that context — and writing about it along the way.