Senior Security Engineer, AI & DevSecOps

Atlas HXM is a global Employer-of-Record provider focused on enabling companies to expand internationally through technology and services. They are seeking a Senior Security Engineer, AI & DevSecOps to help secure AI adoption and build robust security architectures for AI platforms and applications.

Responsibilities:

• Design and implement secure architectures for enterprise AI platforms, AI assistants, AI APIs, and AI-enabled applications
• Build and maintain a secure AI sandbox environment supporting experimentation and responsible AI adoption
• Develop security guardrails for AI-assisted development, including AI-generated code, vibe coding, AI agents, and AI workflows
• Evaluate new AI technologies and recommend secure adoption strategies based on business needs and risk
• Integrate security throughout the Secure Software Development Lifecycle (SSDLC) using automated controls and developer-friendly workflows
• Integrate SAST, DAST, SCA, secret scanning, IaC scanning, and cloud security scanning into CI/CD pipelines
• Secure cloud-native applications, APIs, containers, and AI services across Azure, AWS, and GCP
• Review AI applications, integrations, and AI-generated solutions prior to production deployment
• Perform AI security assessments, threat modeling, and architecture reviews
• Support vulnerability management, incident response, and threat detection involving AI platforms and cloud services
• Support change management, configuration management, documentation, and audit evidence
• Support ISO/IEC 27001, 27017, 27018, and future AI governance initiatives
• Partner with engineering teams to enable secure development while minimizing friction
• Continuously research emerging AI technologies, threats, and best practices

Requirements:

• 7–12+ years of experience in cybersecurity, application security, DevSecOps, cloud security, platform engineering, or related disciplines
• Demonstrated experience securing enterprise AI platforms, AI APIs, AI-assisted development tools, or LLM ecosystems
• Deep understanding of modern AI security concepts, including prompt injection, data leakage, AI supply chain risks, and responsible AI practices
• Strong understanding of how cloud platforms, APIs, identity, data, and AI services integrate to deliver secure enterprise solutions
• Experience integrating security into modern software delivery pipelines using automated testing and policy enforcement
• Hands-on experience with application security, cloud security, vulnerability management, and developer security platforms
• Experience implementing IAM, Zero Trust principles, logging, monitoring, and security automation
• Experience supporting governance frameworks including ISO/IEC 27001, 27017, 27018, NIST CSF, or SOC 2
• Strong automation and scripting skills using Python, PowerShell, Bash, or REST APIs
• Excellent communication skills, with the ability to translate security requirements into practical engineering solutions
• Experience securing AI agents, MCP integrations, RAG solutions, vector databases, or AI orchestration platforms
• Experience implementing AI governance programs and enterprise AI security standards
• Experience performing threat modeling, application security assessments, and architecture reviews
• Experience supporting internal and external compliance audits
• Professional certifications such as CISSP, CCSP, CISM, Azure Security Engineer Associate, or AWS Certified Security – Specialty