At Securonix, we’re on a mission to secure the world by staying ahead of cyber threats and reinforcing all layers of our platform with AI capabilities. Our Securonix Unified Defense SIEM provides organizations with the first and only AI-reinforced solution built with a cybersecurity mesh architecture on a highly scalable data cloud. Enhanced by Securonix EON’s AI capabilities, our innovative cloud-native solution delivers a seamless CyberOps experience, empowering organizations to scale their security operations and keep pace with evolving threats.
Recognized as a five-time Leader in the Gartner Magic Quadrant for SIEM and highly rated on Gartner Peer Insights, our award-winning Unified Defense SIEM provides organizations with 365 days of “hot” data for rapid search and investigation, threat content-as-a-service, proactive defense through continuous peer and partner collaboration, and a fully integrated Threat Detection, Investigation, and Response (TDIR) experience all within a single platform. Built on a cloud-native architecture, the platform leverages the Snowflake Data Cloud for unparalleled scalability and performance.
Securonix is proud to be a cybersecurity unicorn and to be featured in CRN’s 2024 Security 100 list. Backed by Vista Equity Partners, one of the largest private equity firms, with over $100 billion in assets under management, we have a unique advantage in driving innovation and growth. With a global footprint, we serve more than 1,000 customers worldwide, including 10% of the Fortune 100. Our network of 150+ partners and Managed Security Service Providers (MSSPs) enables us to deliver unmatched security solutions on a global scale.
Join us as we redefine cybersecurity, innovate fearlessly, and grow together as one team.
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.
Securonix provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, age, disability, genetic information, marital status, amnesty or status as a covered veteran in accordance with applicable federal, state and local laws.