Overview
Skills
Job Details
This position is 100% remote opportunity within USA. No C2C candidates PLEASE!
AI Security Engineer will serve as a senior technical expert responsible for designing, building, and maintaining AI models and systems that support cybersecurity and information security objectives. This individual contributor s role will focus on the practical application of AI to real-world security challenges, including inventory, threat detection, anomaly analysis, and automation of security operations. The ideal candidate will bring deep technical expertise in AI/ML, a strong understanding of secure system design, and a collaborative mindset to work alongside the Generative AI teams and the GIS teams.
Key Responsibilities:
- AI System Design & Development: Architect, build, and deploy Models, pipelines, and systems that support cybersecurity use cases such as inventory, threat detection, behavioral analytics, and incident response.
- Security-Driven Innovation: Apply AI to automate and enhance security operations, reduce response times, and improve threat intelligence.
- Model Evaluation & Monitoring: Ensure AI models are robust, explainable, and resilient to adversarial threats through rigorous testing and continuous monitoring.
- Data Engineering: Design secure and scalable data pipelines to support model training and inference using structured and unstructured security data.
- Thought Leadership: Serve as a subject matter expert on AI, advising stakeholders and contributing to Marriott s AI strategy.
- Documentation & Governance: Maintain clear documentation of models, methodologies, and outcomes to support transparency, reproducibility, and compliance.
Qualifications:
- Education: Master s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, a related STEM field, or commensurate experience in role.
- Experience: 5+ years of experience in software engineering, data science, or AI/ML development. 2+ years applying AI to cybersecurity, information security, rare event detection, complex path trajectories, graph learning, or related domains.
- Proven experience delivering production-grade AI systems in enterprise environments.
- Strong communication and interpersonal skills, with the ability to convey complex concepts to nontechnical stakeholders.
Technical Skills:
- Deep understanding and experience building AI Systems and Generative AI technologies, models, and platforms.
- Experience in Security Tools and AI/ML frameworks such as PyTorch, TensorFlow, Task and Pipeline Systems, and Agent Frameworks.
- Experience in developing software and models in at least one of the following languages: Python, C++, Go, Java, or Rust.
- Proficiency in security protocols, encryption methods, and vulnerability assessment tools.