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Leads technical pre-sales and post-sales engagements for federal cybersecurity customers. Owns proof-of-value lifecycles, product demonstrations, threat analysis, customer assessments, technical evaluations, and ROI reporting. Advises stakeholders on insider risk, endpoint and cloud security, AI-related risks, and federal compliance. Supports sales pursuits, RFI/RFP responses, technical collateral, enablement, and product improvements while engaging DoD, Federal Civilian, and Intelligence Community customers.

Owns post-sale outcomes for enterprise customers, including onboarding, adoption, customer health, renewals, escalations, QBRs, and expansion opportunities. Builds relationships across security, IT, legal, HR, procurement, and executive teams. Guides customers on insider risk, data protection, and security initiatives while coordinating cross-functional delivery, maintaining account health records, and ensuring evidence-based renewal readiness.

Design, build, deploy, and maintain DTEX’s platform and data pipelines. Develop scalable Python microservices, manage containerized Kubernetes deployments, optimize OpenSearch and PostgreSQL storage, improve search performance, and build big-data analytics features. The role also emphasizes security, data protection, full lifecycle ownership, mentoring, testing, automation, and continuous improvement.

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 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.

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.