AI Cybersecurity Engineer

SEI

AI Cybersecurity Engineer serving as a technical security lead for AI initiatives at SEI. Architecting secure platforms to protect organization against evolving AI-powered threats.

Posted 7/22/2026full-timeRemote • Pennsylvania • 🇺🇸 United StatesSeniorLead💰 $160,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI/ML security principles, including adversarial machine learning and model security, while implementing security frameworks and standards such as OWASP LLM Top 10 and NIST AI RMF. Proven ability to design and architect secure AI systems, integrating security controls throughout the AI lifecycle and ensuring compliance with data governance standards.

Highest-signal resume keywords

AI/ML Security PrinciplesCloud Security ArchitecturesProgramming Languages: Python, Java, C#, GoSecurity Frameworks: OWASP LLM Top 10, NIST AI RMFMLOps/MLSecOps Toolchains

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Applicant Tracking System Keywords

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Hard Skills

Adversarial Machine LearningModel SecurityData Poisoning DetectionSecure Coding PracticesThreat Modeling MethodologiesRisk Assessment FrameworksBehavioral Anomaly DetectionInput/Output FilteringModel Integrity ValidationContinuous Monitoring

Soft Skills

Communication of Technical ConceptsLeadershipStrategic Recommendations

Tools & Technologies

TensorFlowPyTorchScikit-learnHugging FaceDockerKubernetesCI/CD PipelinesAPIsRBACConfidential Computing

Industry Keywords

AI Security GovernanceEthical AI UseModel ValidationBias DetectionExplainability Requirements

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityDockerERPGoGoogle Cloud PlatformJavaKubernetesPythonPyTorchRPAScikit-LearnTensorflow

About the role

Key responsibilities & impact

Design and architect enterprise-grade, secure AI security platforms that protect ML models, training pipelines, inference systems, and AI-driven applications from sophisticated adversarial attacks
Define and drive the technical vision and security roadmap for all AI/ML initiatives across the organization, embedding security into the complete AI lifecycle from development through deployment and monitoring
Lead architectural reviews and provide authoritative technical guidance on security architecture patterns, threat models, and risk mitigation strategies for AI systems
Establish security standards and frameworks for AI development, incorporating OWASP LLM Top 10, MITRE ATLAS, NIST AI Risk Management Framework, and other industry best practices
Develop security controls for AI model training, validation, deployment, and monitoring including input/output filtering, model integrity validation, and behavioral anomaly detection
Implement data security and privacy controls across AI workflows including sensitive data detection, data loss prevention for AI prompts and responses, and confidential computing techniques
Build automated security testing frameworks for continuous validation of AI model security posture and detection of adversarial attack patterns
Engineer AI-powered security detection systems leveraging machine learning for threat hunting, anomaly detection, and behavioral analytics
Communicate complex technical concepts to non-technical executives and business leaders, translating security risks into business impact and strategic recommendations
Serve as the technical authority and trusted advisor on AI security matters for senior leadership including CISO and CTO
Develop and enforce AI security governance policies, standards, and guidelines that ensure ethical, safe, and compliant use of AI across the enterprise
Establish AI model governance frameworks addressing model validation, bias detection, explainability requirements, and audit trails
Implement continuous monitoring and observability for AI systems to detect model drift, performance degradation, and security anomalies in real-time

Requirements

What you’ll need

Bachelor's degree in Computer Science, Cybersecurity, Information Security, Software Engineering, or related technical field preferred
Advanced coursework or specialization in artificial intelligence, machine learning, cryptography, or secure systems design
A minimum or 10 years of progressive experience in cybersecurity engineering, with at least 2+ years focused on AI/ML security, application security, or security architecture
Deep expertise in AI/ML security principles including adversarial machine learning, model security, data poisoning detection, and prompt injection defense
Expert-level knowledge of AI/ML frameworks and platforms (TensorFlow, PyTorch, scikit-learn, Hugging Face) and their security implications
Extensive experience with cloud security architectures on AWS, Azure, OCI, or GCP, specifically securing AI/ML workloads in cloud environments
Strong proficiency in programming languages including Python (primary), Java, C#, Go, or similar with emphasis on secure coding practices
Proven experience designing and implementing security for LLMs and generative AI systems including RAG architectures, vector databases, and agent frameworks
Demonstrated ability to securely integrate AI/ML solutions with existing legacy applications (e.g., ERP, CRM, mainframe, or on-prem systems) using modern integration patterns (APIs, gateways, middleware, or RPA), while enforcing enterprise security controls such as RBAC, encryption, logging, and compliance with data governance standards
Hands-on expertise with MLOps/MLSecOps toolchains, CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure-as-code
Deep understanding of security frameworks and standards: OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, ISO 27001, SOC 2
Strong knowledge of cryptography, authentication/authorization protocols, zero-trust architectures, and identity security principles
Demonstrated experience as a technical lead or architect
Proven track record architecting complex, distributed security systems at enterprise scale with high availability and performance requirements
Extensive experience with threat modeling methodologies and risk assessment frameworks specifically adapted for AI systems.

Benefits

Comp & perks

healthcare (medical, dental, vision, prescription, wellness, EAP, FSA)
life and disability insurance (premiums paid for base coverage)
401(k) match
education assistance
commuter benefits
up to 11 paid holidays/year
21 days PTO/year pro-rated for new hires which increases over time
paid parental leave
back-up childcare arrangements
paid volunteer days
a discounted stock purchase plan
investment options
access to thriving employee networks