Senior​/QA Engineer – Agentic AI Platform

Overview

We are seeking a highly skilled and experienced Senior/Staff QA Engineer to support a critical customer engagement. This role is ideal for a detail-oriented tester who thrives owning quality end-to-end — someone equally comfortable writing precise manual test cases and building automated coverage for a fast-moving agentic AI product.

The successful candidate will work closely with the Delivery Lead/Solutions Architect and customer engineering stakeholders to ensure product quality from initial test planning through final release.

• 5+ years of professional QA experience, with at least 2+ years at a senior or staff level.
• Demonstrated experience testing production software through a full Application Development Lifecycle (ADLC).

• ADLC Expertise: Strong understanding of the Application Development Lifecycle — from requirements through release and support.
• UI/UX Acumen: Solid UI/UX understanding, with the ability to evaluate usability and flag design/interaction issues, not just functional bugs.
• AI Agent Testing: Hands-on experience testing AI Agent use cases — including conversational flows, agent decision-making, tool/function calling, and edge-case or failure-mode behavior.
• Automation Frameworks: Proven experience with automated testing frameworks and building maintainable, scalable test suites.
• Infrastructure Management: Ability to stand up and manage a Playwright cluster to run automated end-to-end (E2E) testing against a live agent platform.
• Autonomy: Ability to independently define clear, well-structured test cases from ambiguous or evolving product requirements.
• Lifecycle Ownership: Experience driving full E2E QA lifecycle ownership: test planning, execution, defect triage, regression, and sign-off.

• Automation Frameworks: Deep expertise with Playwright (including cluster management and parallel execution).
• Languages: Proficiency in JavaScript / Type Script or Python for writing automation scripts.
• AI/LLM Tools: Familiarity with testing LLM outputs, prompt evaluation frameworks, or conversational AI testing tools.
• CI/CD & Dev Ops: Experience integrating automated test suites into pipelines (e.g., Git Hub Actions, Git Lab CI, Jenkins) and working with Docker containerization.
• Defect Tracking & Tools: Proficiency with Git, Jira, and modern test management tools.