AWS & Azure Cloud and Data Architect · Agentic AI Engineering · C#, .NET 10, Python & SQL
I design and build cloud platforms, data products and .NET services that other teams and agents can rely on. I have more than 8 years of experience, and I'm now leading AWS cloud, data and agentic AI engineering.
🌐 kumarchandrachooda.com · 💼 LinkedIn · 📧 kumarchandrachooda@gmail.com
- ⚡ New services set up in 2 days instead of 3 weeks. I built a security-first, zero-trust API framework on AWS that every new web application starts from. It layers Cognito with PKCE, Lambda authorisers, WAF, PrivateLink and KMS over API Gateway on Lambda or ECS.
- 📊 Reports on 100,000 records in under a minute instead of 3. I architected a multi-tenant analytical data product on the medallion architecture: Kinesis, AWS Glue (Spark), Apache Iceberg on Amazon S3 Tables, and Lake Formation tenant isolation with row-level filtering.
- 🤖 Data services delivered 3–5x faster. I lead agentic development with Claude Code. Agent tools and skills carry the platform's own infrastructure rules, and multi-agent workflows take a specification to tested code, ending in human approval.
- 🧱 Nearly 20 services on one delivery model. I was lead engineer for the plug-and-play CI/CD and Infrastructure as Code modules (AWS CDK, Terraform) behind cloud-native development. Before that, I built a Terraform library for Azure that scaled to hundreds of managed deployments across regions and environments.
- 🔐 GDPR built into the platform:
- tombstoning, so a person can be forgotten without losing audit trails;
- masking as data is removed;
- a storage-limitation job that removes data beyond its retention limit across subsystems and domains.
- 🚀 Horizontal scale. I introduced Valkey as a distributed, multi-layer, content-aware cache and standardised caching across the application.
- 🏗️ Legacy to cloud-native. I modernised monoliths, including AS400 and web forms systems, into .NET Core microservices for insurance quoting, agency and policy-document platforms.
- 🧑🏫 People. I've mentored 11 engineers and 5 apprentices, and trained developers to use AI coding agents critically rather than trust them blindly.
| Project | What it is |
|---|---|
| Agentic Development (Lead) | Spec-driven, multi-agent workflows from specification to tested code, with agent tools that know the platform's rules and output fed into RAG for AI chat. Claude Code, MCP, Amazon Bedrock, RAG |
| Multi-Tenant Analytical Data Platform (Architect) | AWS-native bronze and silver layers, with a multi-tenant PostgreSQL gold layer. One EF Core migration set provisions every tenant under database, schema or shared-database isolation. C#, .NET 10, EF Core, MediatR, Glue, S3 Tables, Lake Formation |
| Infrastructure as Code (Lead) | A Terraform library for the Azure estate (App Service, Functions, APIM, AKS, Cosmos DB, Front Door), and AWS CDK modules for every service in the API framework and data product |
| Agent Memory & Knowledge | Hand-built agent loops and harnesses with memory, and documentation served to agents through RAG and an MCP server, with LLM evaluation and guardrails. Python, Strands Agents, LangGraph, Bedrock |
| kumarchandrachooda.com (Architect) | My own platform, built with spec-driven, agentic development: every change starts as a written specification, AI coding agents implement it in parallel Git worktrees, and automated checks gate what they produce. ASP.NET Core on AWS Lambda behind CloudFront, AWS CDK |
| Insurance document platforms (Solution Architect, Lead Developer) | Policy document generation with InRule validation, plus master data management and an operational data store. Azure Functions, .NET, Terraform, API Management, event-driven |
- Agentic AI & LLMs: multi-agent systems, AWS Strands Agents, LangChain, LangGraph, Amazon Bedrock, MCP servers, RAG, vector search, LLM evaluation, guardrails, Claude Code
- Languages & .NET: C#, Python, TypeScript, SQL / T-SQL, PowerShell; .NET 10, ASP.NET Core, EF Core, Dapper, MediatR (CQRS), React, Angular
- AWS: Lambda, ECS Fargate, API Gateway, SQS, EventBridge, Cognito, Kinesis, Glue, Lake Formation, S3 Tables, RDS, DynamoDB, Bedrock, SageMaker, CloudFront
- Azure: App Service, Functions, API Management, AKS, Event Grid, Cosmos DB, Azure DevOps
- Data: medallion lakehouse, star schema, SCD2, Spark (PySpark), Apache Iceberg, change data capture (Debezium), PostgreSQL, SQL Server, MongoDB
- Platform & security: AWS CDK, Terraform, CI/CD, Docker, Kubernetes, OpenTelemetry; zero trust, OAuth 2.0 with PKCE, multi-tenant isolation, GDPR
AWS Certified
- Machine Learning Engineer – Associate
- Data Engineer – Associate
- Solutions Architect – Associate
Microsoft Certified
- Azure Solutions Architect Expert
- DevOps Engineer Expert
- Azure Developer Associate
- MCSA Web Applications
- Programming in C#
- Querying Data with T-SQL
🌱 Currently preparing for Claude Certified Architect (Foundations and Professional).
Education
- MSc Advanced Computer Science (Cloud Computing), University of Leeds, 2023, with Distinction
- B.Tech Computer Science Engineering, JSS Academy of Technical Education, 2016
🤝 Open to conversations about cloud and data architecture, agentic AI in production.