AI Security & Compliance Engineer (AI/ML Security | GenAI Risk | Cloud Security | DevSecOps)

AI Security & Compliance Engineer

AI/ML Security | GenAI Risk | Cloud Security | DevSecOps
Level: Security Specialist / Senior Engineer

Role Overview

We are seeking an AI Security & Compliance Engineer to secure enterprise AI platforms, LLM applications, RAG pipelines and agentic workflows. The role covers GenAI-specific risks, AWS cloud security, DevSecOps, privacy and regulatory compliance.

Key Responsibilities

• Design and review secure architectures for AI platforms, LLM applications, RAG pipelines and model-serving environments.
• Conduct threat modelling and AI red teaming for prompt injection, jailbreaks, data leakage, retrieval poisoning, adversarial attacks and unsafe tool usage.
• Implement AWS security controls covering IAM, encryption, KMS, secrets, networking, APIs, logging and data-loss prevention.
• Embed security into MLOps/LLMOps, Terraform/IaC, Kubernetes, containers and CI/CD pipelines.
• Assess third-party models, APIs, open-source packages and vendors for security, privacy and supply-chain risks.
• Monitor suspicious AI activity, unauthorised access, policy violations and potential data exposure.
• Support vulnerability management, penetration testing, incident response and production-readiness reviews.
• Maintain audit-ready security, compliance, testing and risk-remediation documentation.

Required Skills

• Strong background in cybersecurity, cloud security, application security, DevSecOps or technology risk.
• Experience securing APIs, microservices, containers, Kubernetes, CI/CD pipelines and infrastructure-as-code.
• Strong AWS security knowledge, including IAM, KMS, encryption, networking, secrets management and logging.
• Understanding of LLM and GenAI risks, including prompt injection, adversarial attacks, data leakage, retrieval poisoning and model supply-chain risks.
• Experience with threat modelling, secure SDLC, vulnerability management, incident response and Terraform/IaC controls.
• Ability to implement practical security controls with engineering teams.

Preferred Experience

• Production security experience with AI/ML platforms or GenAI applications.
• Financial services, regulatory compliance, privacy, audit or technology-risk experience.
• Familiarity with AI red teaming, secure RAG, LLM gateways, Power Platform/Copilot Studio governance and data-loss prevention.

Alternate Titles: AI Security Engineer, ML Security Engineer, GenAI Security Engineer, Cloud Security Engineer – AI, DevSecOps Engineer – AI or AI Compliance Engineer.