Jobs at DTEX Systems

Develop and execute manual and automated testing strategies for enterprise software, including functional, performance, interoperability, security, and regression testing. Design and maintain automated test frameworks, apply AI-assisted testing techniques, identify quality risks, and validate software across Linux, virtualized, and cloud environments. Collaborate in technical discussions and contribute QA expertise across complex software platforms.

Provides customer-facing technical support for complex clustered software deployments. Responsibilities include configuring and maintaining production systems, troubleshooting Linux and endpoint environments, resolving installation and connectivity issues, training customers on the product UI, reproducing defects, validating procedures, and collaborating with Sales, Engineering, QA, and Customer Engineering teams.

Analyze customer activity data to identify insider-threat behaviors, patterns, and anomalies; investigate areas of concern; present findings through reports and visualizations; recommend remediation and proactive security measures; and develop behavioral profiles, use cases, and algorithms. The role may also provide customer support for the DTEX platform, coordinate escalated technical support, and collaborate with engineering on product improvements.

Design and implement behavioral detections and analytic content, build full-stack applications and internal tools, develop algorithms for behavioral modeling and risk scoring, lead quality engineering and test automation for intelligence pipelines, collaborate cross-functionally, and research emerging threats and detection methods.

The Insider Risk Analyst analyzes customer data for threat detection, coordinates investigations, presents findings with data visualization, and provides tiered support while enhancing the security environment.

Lead design, implementation, and tuning of large-scale OpenSearch clusters for IRM/DLP products. Mentor engineers, consult with clients, contribute to open-source, migrate Elasticsearch deployments to OpenSearch, optimize ingestion and search performance, and operate cloud-hosted search environments while collaborating with global teams.

Lead backend-focused full-stack development using Python/Django and Postgres/OpenSearch. Architect scalable features, containerized deployments (Docker/Kubernetes) across cloud and on-prem, collaborate with product and frontend (React), ensure security, performance, and reliability, support deployments and operations, and adopt AI-assisted development tools to improve productivity.

Drive modernization of infrastructure by writing Python automation, implementing Terraform-based IaC, using Ansible/SaltStack for config management, building CI/CD pipelines, improving monitoring/alerting, and participating in follow-the-sun on-call incident response to scale and harden customer environments.