Staff SDET (Big Data & Agentic AI)

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.