Role: Expert Automation QA JavaScript Engineer
Experience: 11+ Years
Location: Remote
Employment Type: Haparz Payroll
About the Role
We are looking for an Expert Automation QA JavaScript Engineer to drive quality engineering for enterprise-scale AI platforms and agentic systems. You will build automation frameworks, validate non-deterministic AI behavior, establish release quality gates, and ensure reliability, observability, and performance across modern distributed applications.
Key Responsibilities
- Design, build, and maintain scalable automation frameworks using JavaScript/TypeScript that are adopted across engineering teams.
- Automate API, integration, platform, and end-to-end testing for AI-powered applications.
- Validate platform non-functional requirements including invocation latency (P95), concurrency, queue backpressure, and LLM provider failover.
- Develop automated validation for asynchronous and event-driven workflows, including failure injection, retry handling, idempotency, and eventual consistency.
- Build intelligent validation approaches for LLM-based applications using semantic scoring, statistical assertions, and model variance analysis.
- Leverage Langfuse and OpenTelemetry traces to validate trace completeness, token usage, cost accounting, and anomaly detection.
- Integrate automated quality gates into CI/CD pipelines with regression detection for every release.
- Produce auditable test evidence and quality reports supporting customer milestone sign-offs.
- Collaborate with AI architects and platform engineers to define acceptance criteria, observability, and testability during solution design.
- Maintain mock LLM services, synthetic datasets, and deterministic testing environments for fast and reliable execution.
- Mentor QA engineers and contribute reusable AI testing frameworks, automation standards, and engineering best practices.
Required Experience
- 11+ years of experience in Automation Testing with JavaScript/TypeScript.
- Expertise in API automation and enterprise automation framework development.
- Proven experience testing AI/LLM-powered or other non-deterministic applications.
- Strong understanding of semantic validation, statistical testing, and managing AI model variability.
- Experience testing distributed, asynchronous, event-driven systems.
- Hands-on knowledge of failure injection, resilience testing, eventual consistency, and idempotency validation.
- Experience with CI/CD pipelines such as GitHub Actions or equivalent and implementing automated release gates.
- Strong SQL, debugging, and performance analysis skills.
- Experience with OpenTelemetry, Langfuse, or similar observability platforms is highly desirable.
- Experience with Temporal or similar workflow orchestration platforms is an advantage.
Work Location: Remote
