Artificial Intelligence Cybersecurity Engineer

Sev1Tech • Arlington, VA

73d

About The Position

We are seeking a skilled Artificial Intelligence Cybersecurity Engineer to join our team and ensure the seamless deployment, monitoring, and optimization of AI models in production. Sev1Tech is seeking an AI Integration Engineer to integrate AI models into production systems, ensuring robust performance, real-time monitoring, and secure operations. The AI Integration Engineer will bridge the gap between AI model development and production systems, integrating models into applications, APIs, and infrastructure. This role focuses on building dashboards for real-time and historical model health, detecting data drift, and managing AI logging, while ensuring secure-by-design practices and alignment with business objectives.

Requirements

• 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; knowledge of JavaScript, C++, or Go is a plus for UI or system-level integration.
• 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 (Requirements 1. US Citizenship, 2. Favorable Background Investigation)

Nice To Haves

• 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.

Responsibilities

• Integrate AI/ML models into applications (e.g., web, mobile, IoT) using APIs (REST, gRPC) and platforms like TensorFlow Serving or AWS SageMaker.
• Create real-time and historical dashboards using Grafana, Kibana, or Plotly to monitor model health (e.g., latency, accuracy) and data drift.
• Implement monitoring pipelines with tools like Evidently AI or Weights & Biases to detect data drift and model degradation, triggering alerts as needed.
• Set up logging systems with ELK Stack, OpenTelemetry, or LangSmith to capture AI events, errors, and traces for debugging and auditing.
• Apply secure-by-design principles to protect models and data from vulnerabilities (e.g., adversarial attacks, data leakage) using tools like Adversarial Robustness Toolbox (ART).
• Optimize model inference for performance (e.g., via quantization, edge deployment) and ensure compatibility with cloud (AWS, Azure) or on-premises infrastructure.
• Partner with data scientists to understand model requirements, DevOps for infrastructure alignment, and stakeholders for reporting needs.
• Perform end-to-end testing of AI integrations, including stress testing and validation of dashboard metrics.
• Ensure integrations comply with regulations like GDPR, HIPAA, or NIST AI RMF for secure data handling.

What This Job Offers

• Number of Employees: 501-1,000 employees