Staff SDET (Big Data & Agentic AI)

Role Overview:

We are seeking an experienced Staff Software Development Engineer in Test (SDET) to lead quality engineering across distributed data platforms, microservices, modern web applications, and agentic AI systems.

Key Responsibilities:

Big Data, Backend, and Microservices Testing

• Define end-to-end test strategies for batch, streaming and data-warehouse workloads using technologies such as Spark, Kafka, Hadoop, Hive, HDFS, and Delta Lake.
• Automate data-quality validation using Python, PySpark, Pytest.
• Validate ingestion, transformation, schema evolution, partitioning, reconciliation, completeness, accuracy, freshness, and business rules.
• Test distributed microservices, REST and GraphQL APIs, and event-driven architectures.
• Build API, integration, component, and consumer-driven contract tests using tools such as Postman/Newman, REST Assured, or equivalent frameworks.
• Validate authentication, authorization, backward compatibility, retries, timeouts, circuit breakers, data consistency, idempotency, failure recovery, and service resilience.
• Evaluate scalability, performance, and fault tolerance under production-like traffic and data volumes.

Web and Browser Automation

• Design and maintain scalable test frameworks using Playwright and Cypress.
• Develop reliable end-to-end, API, integration, visual-regression, and accessibility test coverage.
• Use Playwright capabilities such as browser isolation, fixtures, auto-waiting assertions, network interception, API testing, tracing, screenshots, parallel execution, and test sharding.
• Test dynamic, data-driven interfaces and validate consistency across the browser, APIs, microservices, and data stores.
• Improve automation reliability through stable locators, deterministic test data, service virtualization, API mocking, and effective failure diagnostics.

Agentic AI and LLM Testing

• Define evaluation strategies for LLM applications, RAG systems, AI copilots, tool-using agents, and multi-agent workflows.
• Build evaluation datasets from curated, production-derived, edge-case, and adversarial scenarios.
• Measure task completion, accuracy, groundedness, retrieval quality, instruction following, tool selection, structured outputs, state management, and workflow completion.
• Test AI systems for prompt injection, jailbreaks, sensitive-data leakage, hallucination, insecure output handling, excessive agency, and unsafe tool use.
• Validate guardrails, least-privilege access, sandboxing, rate limits, human approvals, and recovery from failed or unexpected actions.
• Implement trace-based evaluation and continuous quality gates for agent decisions, tool calls, latency, errors, token usage, and cost.
• Use Playwright to test browser-capable AI agents, including navigation, form interaction, permissions, approval checkpoints, and error recovery.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software quality engineering, test automation, or software development, including senior technical leadership.
• Strong experience testing distributed data pipelines, microservices, APIs, or event-driven systems.
• Hands-on experience with Spark, Kafka, Hadoop, Hive, or modern cloud-data platforms.
• Advanced programming and automation skills in Python, and JavaScript/TypeScript.
• Strong browser-automation experience with Playwright or Cypress, including framework design, API testing, parallel execution, and CI integration.
• Experience with API contracts, service virtualization, distributed workflows, authentication, and failure handling.
• Experience with CI/CD platforms such as GitHub Actions, GitLab CI, Jenkins, or Azure DevOps.
• Working knowledge of Docker, Kubernetes, Linux, cloud environments, and production observability.
• Strong communication, collaboration, mentoring, and problem-solving skills.