QA Engineer – Creative Automation (100% Remote) (LATAM ONLY)

About AllShore Talent

AllShore Talent partners with growing organizations to build high-performing technology and consulting teams. We connect skilled professionals with meaningful, long-term engagements across web technologies, digital experience platforms, and enterprise software delivery — offering competitive compensation, flexible engagement models, and a collaborative, remote-friendly culture.

About the Role

Adobe Workflows, API Integration and Digital Media

AllShore Tallent is seeking a mid-to-senior QA Engineer specializing in creative automation to validate end-to-end creative automation and digital media production workflows. The role spans Airtable intake and status control, AWS orchestration, Adobe Photoshop APIs, and Frame.io review and approval. The current use case focuses on static banners and Photoshop outputs, with motion graphics and video workflows in the pipeline, including one moving into implementation.

The ideal candidate brings a methodical approach to tracing distributed workflows, finding edge cases, maintaining state integrity, and verifying data isolation, with a background in digital media workflow engineering, ad-tech production pipelines, creative automation, or cloud-native integration QA.

Key responsibilities

• Validate asynchronous, event-driven pipelines in which intake actions trigger background state machines and webhooks. Trace the complete flow from Airtable through AWS and Photoshop APIs to Frame.io.
• Verify idempotency, de-duplication, race-condition handling, and queue throttling, including duplicate Frame.io Approved webhooks.
• Test recovery from network interruptions, expired tokens, corrupt or oversized source media, missing manifest keys, and simulated API service limits. Verify circuit breaker thresholds, queue pausing, slot release, and manual or administrator recovery.
• Design deterministic cache lifecycle tests that distinguish reusable asset-level caches (Creative/DMC) from isolated template-level manifests. Confirm that template timestamp changes and asset re-uploads invalidate caches correctly and prevent stale file delivery.
• Reconcile assets, folders, and version stacks. Test URL-encoded filenames, duplicate same-name folder structures, version stack collisions, and protection of active in-progress uploads from deletion.
• Validate AI cropping and graphical transformations across human and non-human subjects in landscape and portrait source files. Assess bounding-box and focal-point detection, identify unnecessary Firefly Generative Expand versus appropriate native cropping, and verify masks preserve native boundaries.
• Inspect typography, font substitutions, leading, multi-line wrapping, bold ranges, safe-zone margins, CTA button bounds, disclaimer visibility, and ratings bug placement across aspect ratios.
• Document reproducible, step-level defects in Jira Cloud with complete asset and log context, and evaluate results against acceptance criteria associated with Epics, Stories, and Bugs.