Staff SDET (Big Data & Agentic AI)

Lead quality engineering and define end-to-end test strategies for big data workloads, microservices, APIs, and event-driven systems using technologies like Spark, Kafka, Hadoop, Hive, and Delta Lake.

Automate data-quality validation and build scalable test frameworks for web, browser automation, and AI agent systems using tools such as Python, PySpark, Playwright, and Cypress.

Develop and implement evaluation methods for agentic AI, LLM applications, and AI systems focusing on security, reliability, and performance metrics including prompt injection and tool usage monitoring.

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.

8+ years of experience in software quality engineering, test automation, or software development with senior technical leadership.

Proficiency with big data platforms (Spark, Kafka, Hadoop, Hive) and modern cloud data platforms, plus advanced skills in Python and JavaScript/TypeScript for automation.

Strong experience with browser automation tools (Playwright or Cypress), API testing, CI/CD platforms (GitHub Actions, GitLab CI, Jenkins, Azure DevOps), and production technologies (Docker, Kubernetes, Linux, cloud, observability).

Experienced in leading testing strategies and automation for distributed data platforms and microservices in complex production environments.

Skilled in integrating testing frameworks across both backend systems and front-end/browser interfaces, including AI/agentic systems.

Capable of designing robust evaluation criteria for AI applications emphasizing security, resilience, and operational monitoring within a continuous integration context.