Chick-fil-A Corporate
A maintainable feedback system joining browser automation, API validation, visual testing, authentication, cloud environments, and CI.
- My role
- Software Engineer in Test
- Context
- Enterprise e-commerce environment
- Period
- 2018–2020
- Employer
- Chick-fil-A Corporate
01 / Challenge
The delivery problem.
Quality feedback crossed browsers, APIs, visual behavior, SSO authentication, and cloud-hosted environments, making isolated test suites difficult to operate as one reliable system.
Who needed it: E-commerce engineering teams investigating application failures and deciding whether changes were ready to release.
02 / Approach
What I personally built.
- 01
Designed modular browser smoke and regression suites with parallel execution, network stubbing, and flaky-test mitigation.
- 02
Built API coverage with Postman and browser automation using contract tests, schema validation, and dynamic data assertions.
- 03
Integrated Applitools Eyes across resolutions, devices, and browsers and automated OIDC and Okta MFA flows.
- 04
Connected GitHub Actions, execution evidence, and AWS resources for repeatable execution and investigation.
03 / Outcome
What changed.
Moved useful feedback earlier in delivery while keeping browser, API, visual, authentication, and environment evidence available for investigation and release decisions.
- Modular smoke and regression automation
- API contract and schema validation
- Cross-browser visual regression coverage
- Automated enterprise authentication workflows
04 / Systems & decisions
APIs, data, and infrastructure.
Browser automation and Postman exercised REST service contracts, schemas, and data-dependent application behavior.
OIDC, Okta MFA, and SSO added authentication dependencies to end-user workflows.
GitHub Actions supplied execution evidence; AWS EC2, S3, and Aurora supported test environments.
Constraints and tradeoffs
- Network stubbing isolated application behavior from external dependencies; checks against real services were still needed to investigate integration failures.
- Headless and parallel execution supported repeatable feedback, while screenshots, video, retries, and timings supplied context when a run failed.
05 / Evidence
What you can inspect.
Documented engineering outputs
The career record documents reusable JavaScript tooling, REST checks, authentication investigations, and CI diagnostic artifacts. Employer repositories and run artifacts are private; no performance improvement percentage is claimed.
How this supports my FDE direction
Investigating APIs, identity, application behavior, and cloud environments built the cross-system debugging skills needed for customer-facing implementation work.
06 / Toolkit
Tools in context.
This account is derived from documented career responsibilities. Client-sensitive details are intentionally generalized, and no undisclosed metrics are presented.