FREE ACCESS
5,000–10,000 jobs/day
See all jobs on JobTailor
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.
AI Security Engineer
Euna SolutionsAI Security Engineer focusing on securing AI/ML systems in a hybrid role at Euna Solutions. Collaborating with various teams to drive implementation, automation, and compliance across AI/ML development lifecycle.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in assessing and mitigating security risks specific to AI/ML systems, implementing security processes across AI/ML pipelines, and ensuring compliance with industry standards. Proven ability to drive cross-functional security initiatives and develop technical security documentation for AI systems.
Highest-signal resume keywords
AI/ML Security Risk AssessmentSecurity Architecture and ImplementationGitOps ImplementationSecurity Tooling and Automation DevelopmentCompliance and Audit Support
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Security ArchitectureAppSec Core DomainsAI Governance InitiativesContinuous SecurityMicroservice ArchitectureCloud-Native ApplicationsServerless Application ArchitectureTechnical Security DocumentationRisk AssessmentAdversarial Attack Mitigation
Soft Skills
Cross-Functional CollaborationProject OwnershipCommunication
Industry Keywords
OWASP LLM Top 10MITRE ATLASNIST AI RMFEU AI ActAgentic AI ArchitecturesMulti-Agent CoordinationTool Orchestration
Tech Stack
Tools & technologiesCloudSDLC
About the role
Key responsibilities & impact- Assess and mitigate security risks specific to AI/ML systems — including model integrity, data poisoning, prompt injection, adversarial attacks, and agentic AI threat vectors
- Implement and maintain security processes, tooling, and automation across AI/ML pipelines and infrastructure
- Define and enforce secure AI development and delivery practices across the SDLC
- Evaluate and help secure agentic AI systems, including multi-agent architectures, tool-use frameworks, and autonomous decision-making pipelines
- Contribute to AI governance initiatives, including policy development, risk assessments, and responsible AI frameworks aligned with regulatory and industry standards
- Partner cross-functionally to embed AI security controls across engineering and operations teams
- Own AI security projects end-to-end, from conception through delivery
- Develop and maintain technical security documentation for AI systems and models
- Support compliance initiatives, audits, and technical assessments relevant to AI/ML environments
Requirements
What you’ll need- Minimum 7-10 years of experience in a hands-on security architecture and engineering role in an agile SaaS development organization
- Proven success driving cross-functional security initiatives in an agile SaaS development organization
- Solid foundation and experience in AppSec core domains
- Direct, hands-on, end to end, experience with Security architecture and implementation in context of microservice, cloud-native, and serverless application architectures
- GitOps implementation, security, and utilization
- Security tooling and automation development, as software
- Continuous security and compliance
- Recent hands-on exposure to securing AI/ML environments
- Working familiarity with AI/ML security risks and frameworks — OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act. You don’t need to have lived in these for years; you need to understand what they’re solving for
- Awareness of agentic AI architectures and the risks that come with them — autonomous agents, tool orchestration, memory systems, multi-agent coordination
Benefits
Comp & perks- Competitive wages
- Wellness days
- Community Engagement Committee
- Flexible workday
- Health and dental benefits
- Culture committee