Kalidas
Kanniappan
I architect the platform other teams ship on.
AI-native, cloud-scale systems at Fortune-500 scale. Currently at Nike — Module Federation shells, event-driven Java services, and agentic engineering with Claude Code & MCP in production.
- Microfrontend Architecture
- Module Federation
- React · Next.js
- Java Spring WebFlux
- AI-Native Engineering
- AWS Serverless
- Event-Driven Systems
- Web Experimentation
System overview
Fifteen years spent turning tangled systems into platforms teams can build on.
I'm a Lead Software Engineer with 15+ years architecting and shipping cloud-native systems at Fortune-500 scale. At Nike, I drive Microfrontend architecture with Module Federation, build complex React SPA + SSR / Next.js monorepo applications, and power them with Java Spring WebFlux microservices on AWS Lambda, Step Functions, DynamoDB, and S3. I own the Web Experimentation platform built on Adobe Experimentation APIs. I'm an early adopter of AI-driven development — production workflows built around Claude Code, Cursor, MCP servers, custom Skills, RAG-backed memory, and Spec-Driven Development with OpenSpec — using AI to accelerate delivery while raising the bar on code quality, observability, and contract discipline.
- role
- Lead Software Engineer
- focus
- Platform · AI-Native
- based
- Beaverton, Oregon
- since
- 2009
- domains
- FinTech · Retail · Sportswear
- edu
- B.E. CS · Anna University
The remotes I've shipped
Nike Web Platform
liveArchitected Nike's Shell Application — a unified React + Next.js host in a monorepo providing the runtime shell, shared design system, auth, telemetry, and routing for dozens of product surfaces across nike.com. Built Microfrontend platform using Module Federation and the Experimentation runtime integrated with Adobe APIs.
Walmart Data Platform
featuredBuilt Java backend APIs and React dashboards powering Customer Experience analytics at Walmart's Data Ventures domain. Designed event-driven architectures using Kafka, CQRS, Event Sourcing, and Saga patterns. Built Looker dashboards on curated data marts with LookML models.
AI-Native Engineering Platform
featuredPioneered production-grade AI-native workflows at Nike — building MCP servers exposing internal tooling, authoring reusable Skills encoding engineering standards, and establishing team-wide agentic development practices with Claude Code and Cursor IDE.
Microservices & API Platform
featuredDesigned and implemented robust API platforms across multiple paradigms: HTTP REST + OpenAPI 3 for external contracts, GraphQL at the edge, tRPC for type-safe internal calls, and gRPC for low-latency service-to-service communication. Established API governance patterns across dozens of consuming squads.
Module Federation Architecture
Architected and implemented micro-frontend solutions using Module Federation, enabling product teams to run A/B and multivariate experiments as independently-deployable React remotes without coupling to the shell's release cycle.
FIS Multi-Tenant Banking Application
Designed and developed multi-tenant support applications using Java Spring Framework, JPA-Hibernate, and IBMMQ for FIS Global. Worked with System Engineers on requirement reviews, creating sequence and flow diagrams for enterprise banking systems.
The stack, registered
select a module to highlight its capabilities
Event log
career.log — an append-only stream of 9 events. Fold left to derive present state.
Architecting and scaling Nike's Web Platform — driving Microfrontend architecture with Module Federation, building AI-native engineering workflows with Claude Code and MCP, and owning the Experimentation platform that validates product ideas with live traffic across nike.com.
- Architected Nike's Shell Application — a unified React + Next.js host in a monorepo providing the runtime shell, shared design system, auth, telemetry, and routing for dozens of product surfaces across nike.com
- Designed monorepo conventions (workspace boundaries, shared dependency strategy, build caching, type-safe contracts) so independent product teams could ship into the shell without breaking each other
- Designed and shipped a Microfrontend platform using Module Federation enabling product teams to run A/B and multivariate experiments as independently-deployable React remotes, decoupled from the shell's release cycle
- Built the Experimentation runtime integrated with Adobe Experimentation APIs, ensuring SSR/CSR consistency, reliable exposure events, and per-member assignment with failure fallbacks
- Designed APIs across multiple paradigms: HTTP REST + OpenAPI 3 for external contracts, GraphQL at the edge, tRPC for end-to-end type-safe internal calls, and gRPC for low-latency service-to-service communication
- Established API governance patterns — versioning, deprecation, Pact CDC contract testing, rate-limiting, idempotency, and pagination — scaling cleanly across dozens of consuming squads
- Adopted Claude Code and Cursor IDE as core agentic coding environments for production Nike workflows — multi-file refactors across React Microfrontends, Java Spring services, and Terraform modules from a single agentic interface
- Expert practitioner of Contextual Engineering — designing system prompts, tool schemas, and retrieved context so agents reason against accurate state rather than hallucinating
- Built and integrated MCP servers exposing Nike-internal tooling (service catalogs, AWS state, observability dashboards) with read-first / write-gated enterprise security patterns
- Authored reusable Skills encoding Nike's engineering standards — React patterns, Spring WebFlux conventions, GitHub Actions playbooks — enforced uniformly across all engineer agents
- Established team-wide AI-native development practices: workspace setup, permission scoping, audit trails, and review checkpoints ensuring AI velocity remained safe and auditable at enterprise scale
Open a connection
Platform architecture, AI-native workflows, or a hard scaling problem — I'm happy to talk.