Artificial Intelligence Cybersecurity Engineer
On-siteArlington, Virginia, United States
Job Summary
Integrate AI/ML models into production applications and APIs using TensorFlow Serving or AWS SageMaker. Build real-time and historical dashboards with Grafana or Kibana to monitor model health and detect data drift. Implement monitoring pipelines using Evidently AI or Weights & Biases to trigger alerts for model degradation. Set up logging systems with ELK Stack or OpenTelemetry to capture AI events and traces. Apply secure-by-design principles to protect models from adversarial attacks and data leakage. Optimize model inference for performance and ensure compatibility with cloud or on-premises infrastructure. Partner with data scientists, DevOps, and stakeholders to align model requirements and reporting needs. Perform end-to-end testing including stress testing and validate dashboard metrics. Ensure integrations comply with regulations like GDPR, HIPAA, or NIST AI RMF. Maintain Department of Homeland Security EOD clearance eligibility.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field
- 4+ years in software engineering or AI integration, with experience deploying AI models in production
- Hands-on experience with dashboarding tools (e.g., Grafana, Kibana) and observability platforms (e.g., Prometheus, Datadog)
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for AI deployment
- Proficiency in Python
- Experience with containerization (Docker, Kubernetes) and API development (REST, GraphQL)
- Expertise in logging frameworks (e.g., ELK Stack, OpenTelemetry) and visualization tools (e.g., Plotly, Chart.js)
- Understanding of AI model metrics (e.g., F1 score, latency) and drift detection techniques (e.g., PSI, KS test)
- Knowledge of AI vulnerabilities (e.g., prompt injection, model inversion) and mitigation strategies (e.g., differential privacy, ART)
- Strong problem-solving skills for debugging integration issues and optimizing dashboards
- Excellent communication to translate technical metrics into business insights
- Collaboration skills to work across data science, DevOps, and product teams
- Must be eligible to obtain a Department of Homeland Security EOD clearance
- US Citizenship
- Favorable Background Investigation
Desired Qualifications
- knowledge of JavaScript, C++, or Go is a plus for UI or system-level integration
- Experience with LLM-specific tools like LangSmith or Helicone for monitoring generative AI applications
- Familiarity with compliance frameworks (e.g., NIST AI RMF, OWASP AI Security Top 10)
- Engagement with AI/ML communities, such as X platform discussions on #AISecurity or #MLOps
Additional Requirements
- Must be eligible to obtain a Department of Homeland Security EOD clearance (Requirements: 1. US Citizenship, 2. Favorable Background Investigation)
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