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Euna SolutionsPosted 1 week ago

Senior Security Engineer - AI Focus

RemoteUnited States

Full TimeSenior LevelMedium

Job Summary

Assess and mitigate security risks specific to AI/ML systems, including model integrity, data poisoning, prompt injection, and adversarial attacks. Implement and maintain security processes, tooling, and automation across AI/ML pipelines and infrastructure while defining secure development and delivery practices across the SDLC. Evaluate agentic AI systems, contribute to governance initiatives, and partner cross-functionally to embed controls within engineering and operations teams. Own AI security projects end-to-end, from conception through delivery, and develop technical documentation for AI systems. Support compliance initiatives and audits relevant to AI/ML environments. This role reports to the Director of Security Engineering & Operations and requires a minimum of 7-10 years in security architecture within an agile SaaS organization. Preference is given to candidates in the EST time zone.

Required Qualifications

  • 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
  • Direct, hands-on, end to end, experience with GitOps implementation, security, and utilization
  • Direct, hands-on, end to end, experience with Security tooling and automation development, as software
  • Direct, hands-on, end to end, experience with 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
  • Awareness of agentic AI architectures and the risks that come with them — autonomous agents, tool orchestration, memory systems, multi-agent coordination

Desired Qualifications

  • Direct experience with LLM security, model red-teaming, or AI threat modeling
  • Hands-on work securing agentic AI systems (e.g., LangChain, AutoGen, CrewAI, or similar frameworks)
  • Experience contributing to or implementing AI governance programs, risk registers, or responsible AI policies
  • Experience with security incident response in AI/ML environments with AI/ML workloads
  • Familiarity with AI governance principles: model transparency, explainability, bias/fairness considerations, and data lineage
  • Relevant certifications, e.g. ISC2 (AI Security, CISSP, CCSP, CSSLP, ISSAP, ISSEP)

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