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ECS · 1 day ago

AI Cybersecurity Engineer

Arlington, VA

Full-time

Onsite

Mid, Senior Level

4+ years exp

ECS is a leading mid-sized provider of technology services to the United States Federal Government. They are seeking a skilled AI Cybersecurity Engineer to ensure the secure deployment, monitoring, and optimization of artificial intelligence models across production environments, bridging the gap between AI model development and operational systems.

Artificial Intelligence (AI)Cloud InfrastructureComplianceConsultingCyber SecurityInformation TechnologyMachine LearningSecuritySoftware

No H1B

U.S. Citizen Only

Responsibilities

Integrate AI/ML models into enterprise applications (e.g., web, mobile, IoT) using APIs such as REST or gRPC and serving frameworks like TensorFlow Serving or AWS SageMaker

Design and implement real-time and historical dashboards using Grafana, Kibana, or Plotly to monitor model health indicators such as latency, accuracy, and utilization

Implement automated pipelines using tools such as Evidently AI or Weights & Biases to detect data drift and model degradation, generating alerts for rapid remediation

Logging and Tracing: Configure comprehensive logging and tracing systems using ELK Stack, OpenTelemetry, or LangSmith to capture AI events, system traces, and error logs for debugging, auditing, and compliance

Apply secure-by-design and adversarial resilience practices to safeguard AI models from threats such as data leakage, prompt injection, or model inversion attacks. Utilize frameworks such as the Adversarial Robustness Toolbox (ART)

Optimize model inference performance through techniques like quantization or edge deployment while ensuring compatibility with hybrid and cloud infrastructures (AWS, Azure, or on-premises)

Partner with data scientists, MLOps, and DevSecOps teams to align model integration with infrastructure, security, and business requirements

Conduct end-to-end testing and validation of integrated AI systems, including stress tests and verification of dashboard accuracy

Ensure integrations adhere to standards such as GDPR, HIPAA, FedRAMP, and NIST AI Risk Management Framework (AI RMF) for secure and ethical AI operations

Qualification

AI integrationCybersecurityObservability toolsCloud platformsPythonContainerizationAPI developmentAI model performance metricsAI vulnerabilitiesAnalytical skillsProfessional certificationsCommunication skillsCollaboration skills

Required

Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related discipline

Minimum 4+ years of experience in software engineering, AI integration, or cybersecurity, including production-level AI model deployment

Hands-on experience with observability and dashboard tools such as Grafana, Kibana, Prometheus, or Datadog

Familiarity with major cloud platforms (AWS, Azure, or Google Cloud) for AI model serving and orchestration

Proficiency in Python; additional experience in JavaScript, C++, or Go preferred

Experience with containerization and orchestration (Docker, Kubernetes) and API development (REST, GraphQL)

Knowledge of logging frameworks (ELK Stack, OpenTelemetry) and visualization tools (Plotly, Chart.js)

Understanding of AI model performance metrics (e.g., F1 score, precision, recall, latency) and drift detection methods (e.g., Population Stability Index, KS test)

Knowledge of AI-specific vulnerabilities such as prompt injection, model inversion, and adversarial attacks, along with mitigation methods (e.g., differential privacy, model hardening, ART)

Strong analytical and problem-solving capabilities for debugging complex integrations and optimizing performance

Effective communication skills to convey technical insights and system health metrics to technical and business audiences

Proven collaboration skills across multidisciplinary teams including Data Science, DevOps, and Cybersecurity

Must be U.S. Citizen and eligible to obtain a Department of Homeland Security (DHS) EOD clearance (requires a favorable background check)

Preferred

Experience with LLM-specific observability tools such as LangSmith, Helicone, or similar platforms for generative AI monitoring

Familiarity with AI security and compliance frameworks such as the NIST AI RMF, OWASP AI Security Top 10, and Zero Trust AI principles

Knowledge of federated learning, edge AI security, or trusted AI pipelines

Engagement with professional AI and cybersecurity communities (e.g., MLOps, #AISecurity, #MLSecOps) for continuous learning and innovation

Professional certifications such as AWS Certified Security - Specialty, Azure Security Engineer, CompTIA Security+, or Certified Ethical Hacker (CEH)

Company

ECS

Glassdoor3.6

ECS is a fast-growing 4,000-person, $1.2B provider of advanced technology solutions for federal civilian, defense, intelligence, and commercial customers.

Founded in 2001

Fairfax, Virginia, USA

1001-5000 employees