Karthik Kodati · Architecture of Confidence
Quality Engineering Architect and Senior SDET with 9+ years in enterprise test automation: Playwright and TypeScript frameworks for global Workday, Kafka event validation for financial systems, CI/CD quality gates, and mobile. Now combining deterministic automation with responsible AI.
01 / 06 · Release confidence, in order
Every release I stand behind rests on six layers, executed from the foundation up: UI and mobile automation, API and integrations, event streams, observability, quality gates, and AI-augmented workflows on top.
Featured case studies
Architecture of a scalable Playwright and TypeScript framework covering Workday HCM, Payroll, Finance, and Integrations across countries and tenants.
QA leadership for financial systems built on Kafka event streams, using observability data and automated quality gates to keep releases trustworthy.
Leadership of a test automation transformation with a reported 40% reduction in test execution time.
Reported 40% reduction in test execution time
What I architect
Automation frameworks treated as production software: layered page objects, typed fixtures, configuration per country and tenant, and parallel cross-browser execution.
Coverage below the UI, where business rules actually execute. REST and SOAP validation alongside the end-to-end flows that depend on them.
Validation of Kafka event streams in financial systems, with observability data used to trace and debug behaviour across services.
Automated checks that run on every change and give teams a clear signal about whether a build is ready to release.
Android and iOS automation integrated with continuous integration, with ownership of coverage and release quality.
Combining deterministic automation with responsible AI: test-generation workflows, API testing assistance, and engineering tooling that keeps humans accountable.
How I work
Coverage is chosen for the risk it retires, not for the number of tests it adds.
They get architecture, code review, type safety, and maintenance like any other system.
Quality signals are designed into the pipeline from the first commit, not bolted on before release.
Maintainable, debuggable systems are preferred over shortcuts that are hard to diagnose later.
AI tooling supports engineering decisions. It does not replace the engineer who is accountable for them.
Career
Zensar Technologies
Architected a scalable Playwright and TypeScript automation framework for global Workday HCM, Payroll, Finance, and Integrations.
Mphasis
Client: JPMorgan Chase
Led QA work on financial systems involving Kafka event streams, observability, debugging, and automated quality gates.
SMARTnCODE
Led a test automation transformation, with a reported 40% reduction in test execution time.
Exaze
Worked on Android and iOS automation, continuous integration, test coverage, and release-quality ownership.
Progment
Progressed through engineering and QA leadership roles, establishing automation and quality practices for enterprise and public-sector systems.
I’m interested in senior roles where test architecture, delivery quality, and hands-on engineering all matter.