• Work closely with Product, UX, Customer Success, and Security engineers to establish user acceptance criteria for new external and internal features. • Develop and automate test cases for functional testing to ensure the software meets quality standards. • Build and maintain dependable test automation using Playwright. • Provide guidance to the Engineering and Product teams on implementing effective test strategies to maintain high-quality standards. • Develop and maintain test data and test environments.

• Design and execute test plans for A.I and Machine Learning driven features including classification, summarization, anomaly detection, and autofill systems • Develop Python-based automation and evaluation scripts to validate model performance, reliability, and output quality • Test LLM-based features for accuracy, guardrail effectiveness, hallucination risk, and behavior under edge cases • Validate data pipelines, input/output transformations, and model integration points across Keeper’s platform • Conduct regression testing on ML models and AI workflows to ensure reliability across releases • Test enterprise-scale behavior analysis features driven by data from ARAM, PAM, and session recordings • Validate security, privacy, and zero-trust requirements for AI model interactions and data handling • Collaborate with ML engineers and cross-functional teams to identify defects and improve model behavior • Analyze logs, metrics, and model outputs to detect anomalies, performance issues, or silent failures

• Validate database functionality, data structures, and backend data flows across the Keeper platform and encrypted vault • Test CRUD operations, schema updates, migrations, indexing behavior, and cross-service data interactions • Verify data integrity, consistency, and correctness across distributed systems and cloud environments • Execute SQL queries to validate stored data, relationships, constraints, and backend processing logic • Review and test schema changes, stored procedures, triggers, and database-level logic from a QA perspective • Analyze logs, query results, and backend output to identify defects or anomalies • Conduct regression testing related to database updates, schema changes, and backend releases • Validate database performance characteristics and query responsiveness in collaboration with engineering teams • Evaluate vault-level workflows that impact stored records, metadata, and encryption-related data handling • Document defects, test results, and reproducible steps clearly in Jira and related tools • Participate in reviews of data-handling requirements, edge cases, and system behaviors

• Develop, execute, and maintain comprehensive test plans and test cases for PAM and platform-level KSM integrations • Perform integration testing across cloud providers (AWS, Azure, GCP), IAM platforms (Okta, Ping Identity, Active Directory), and CI/CD systems (Jenkins, GitLab, Azure DevOps) • Validate PAM functionality across Windows, Linux, databases, and hybrid infrastructure environments • Identify, document, and validate defects, collaborating with engineering and product teams to drive resolution • Execute security-focused validation workflows to ensure expected access controls, policy enforcement, and audit behaviors • Perform reliability, stress, and fault-tolerance testing for PAM services and workflows • Analyze logs, errors, and system behavior to diagnose failures and identify root causes • Contribute to automated test coverage in collaboration with engineering teams • Recommend improvements to enhance product usability, resilience, and security • Maintain clear documentation of testing procedures, results, and reproducible steps • Stay current with industry trends and best practices in privileged access and secrets management