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We are redefining the travel industry with a truly autonomous platform powered by proprietary Agentic AI. As an Automation Engineer, youll play an essential part in building and scaling the testing infrastructure that validates our mission-critical AI workflows. This is a high-scale environment where you will use Cypress to solve unique challenges in autonomous decision-making, collaborating globally to deliver a platform trusted by major enterprises.
What Youll Do:
Architect the Cypress E2E Framework: Design, build, and scale a robust, high-performance end-to-end automation framework using Cypress to validate our core web application workflows, ensuring the complex UI accurately reflects the autonomous decisions made by our AI agents.
Validate Autonomous Logic via the UI: Develop sophisticated test harnesses within Cypress that interact with the application and perform data validation (e.g., intercepting network requests) to verify the intricate decision-making, cost optimization, and safety constraints of our self-governing AI agents.
Drive CI/CD Velocity: Take ownership of the testing lifecycle by integrating fast-running, automated Cypress tests directly into our CI/CD pipelines, serving as the final, reliable gate that allows the engineering team to deploy multiple times daily with zero functional regressions.
Performance and API Testing: Utilize Cypress's capabilities for API-level testing to quickly validate backend microservices, augmenting UI tests where necessary to maintain speed and reliability.
Contribute to Engineering Culture: Champion best practices in testability, reliability, observability, and code coverage, mentoring fellow engineers and fostering a culture of technical excellence across the platform.
Solve Unique Problems: Apply deep technical expertise and creativity to address novel testing challenges related to LLMs, such as ensuring the AI-generated UI flows are robust and predictable.

We are seeking a QA Engineer with a strong passion for data quality, performance, and scale to join our Data Platform team.
This role is ideal for a QA professional who enjoys working close to complex data systems, understands large-scale pipelines, and wants to play a key role in shaping the automation and quality strategy of a data engineering organization.
You will act as the primary quality owner for high-volume, mission-critical data platforms, working closely with data engineers, backend developers, and platform teams.
What Youll Do:
Data Quality & Validation:
Design and execute data validation strategies for large-scale batch and streaming pipelines
Ensure data correctness, completeness, freshness, and consistency across the data lake
Define and automate checks for schema changes, data drift, and data quality regressions
Performance & Scalability Testing:
Plan and execute performance and scalability tests for data pipelines and processing jobs
Identify bottlenecks across ingestion, transformation, and querying layers
Partner with engineers to validate performance improvements and prevent regressions
Automation & Infrastructure:
Develop and maintain the data teams QA automation infrastructure
Build reusable testing frameworks and tools tailored for large datasets and pipelines
Integrate automated tests into CI/CD pipelines and production monitoring workflows
Collaboration & Ownership:
Work closely with data engineers, backend developers, and platform engineers throughout the development lifecycle
Act as the sole QA owner within a cross-functional team, driving quality without becoming a bottleneck
Participate in design discussions to ensure testability and observability are built in from the start
Quality Mindset & Communication:
Champion a quality-first culture within the team
Clearly communicate risks, findings, and quality metrics to technical stakeholders
Balance thoroughness with pragmatism in fast-moving, high-scale environments.