Security Vulnerability Engineer (R-00224)

Job Responsibilities

• Vulnerability Management: Identify, assess, and prioritize vulnerabilities across
  enterprise systems; develop and tune detection logic and analytics that meet defined
  performance and coverage standards.
• Threat Detection Engineering: Design, develop, and implement detection and
  enrichment systems that analyze large volumes of unstructured security telemetry, logs,
  and threat-intelligence data.
• Technical Leadership: Lead security engineering projects with a focus on detection,
  vulnerability analytics, and emerging defensive technologies.
• Predictive Risk Modeling & Forecasting: Configure data pipelines and telemetry
  ingestion processes and implement predictive components that analyze five or more years
  of historical incident and vulnerability data to generate time- and location-based risk
  forecasts.
• Systems Integration: Integrate detection and vulnerability-management solutions with
  existing SIEM, ticketing, and operational systems to ensure seamless data flow and
  usability within current workflows; collaborate with cross-functional teams, including work
  within the STRIDE platform.
• Validation & Accuracy: Validate data integrity, detection performance, and system
  reliability across security tooling; assess detection and forecast accuracy, ensure
  alignment between predicted and observed threat patterns, and verify outputs are
  operationally meaningful for command staff and field leadership.
• Performance Management: Monitor, evaluate, and continuously improve detection and
  vulnerability-analytics performance; identify optimization opportunities and tune for scale,
  efficiency, and low false-positive rates in cloud environments.
• Tool Utilization: Leverage common security and analytics tooling (SIEM, vulnerability
  scanners, AWS security services, TensorFlow, PyTorch) and custom frameworks for
  specialized detection applications.
• Governance & Risk: Assess model and detection risks, biases, and coverage gaps in accordance with responsible-use guidelines and regulatory requirements.
Detection Operations (DetOps/MLOps): Implement practices to automate deployment,
monitoring, and lifecycle management of detections, analytics, and models.

Job Qualifications

• Experience: Minimum of 5 years in security engineering, vulnerability management, or
  detection engineering, spanning design, evaluation, and deployment.
• Citizenship: U.S. citizenship required; must be willing to undergo a U.S. Government
  background investigation.
• Technical Proficiency: Hands-on experience with security analytics and detection
  frameworks, scripting/automation (Python), and major cloud platforms; familiarity with
  PyTorch, TensorFlow, Keras, Hugging Face, LangChain, and API-driven tooling for
  analytics is a strong plus.
• Data Management: Experience with large-scale data stores, search/vector databases
  (Pinecone, Weaviate, Qdrant, Chroma), and retrieval-based analysis architectures for
  security use cases.
• Advanced Analytics: Advanced query and detection engineering, model/detection tuning,
  and hands-on experience with analytics and automation tooling.
• Evaluation: Experience in detection and model evaluation, monitoring, validation,
  benchmarking, and deployment

Originally posted on Himalayas