We are building a new test automation practice from the ground up for an enterprise client. This is a greenfield initiative: a newly designed Playwright-based automation framework is being rolled out across the client's entire QA organization, with the goal of lifting automated coverage from near-zero to 60–70%. Automated tests are delivered inside the same two-week sprint as the feature code they cover. Apply now.
Key Responsibilities
- Build out the automation framework alongside the Lead Architect.
- Apply the framework retroactively across the existing codebase to lift automated coverage toward the 60–70% target.
- Support other QA engineers as they adopt the new framework.
- Deliver automated tests within the same sprint as the feature code they cover.
- Production Reliability & Monitoring: Ensure ongoing model scalability, reliability, and robust monitoring in production environments.
- Performance & Cost Optimization: Proactively identify and implement strategies to optimize both the computational performance and operational costs of AI systems.
Required Qualifications
- An engineering background moving into QA automation.
- 5+ years of test automation or software engineering experience.
- Hands-on experience with Playwright
- Comfort working across multiple stacks/surfaces, including web and ideally Salesforce.
- Strong spoken and written English.
- A proactive, self-directed style: comfortable flagging blockers, communicating async, and taking initiative in a fast-moving greenfield project.
- Experience with system integrations and orchestration.
- Strong communication skills, with the ability to articulate complex data science concepts and architectural trade-offs to client-side technical leadership (CTOs, Lead Data Scientists).
Nice to Have
- Experience with open-source model deployment (Llama 3, Mistral) and fine-tuning techniques.
- Familiarity with managed cloud AI services (AWS SageMaker, Vertex AI, or Azure AI).
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