AI Security Engineer

Job description

**Job Title: AISecurity Engineer** **Role Overview** We are seeking askilled **AI Security Engineer** to help design, implement, and maintainsecure cloud-native AI platforms and applications. This role focuses onsecuring AI/ML workloads, cloud infrastructure, APIs, data pipelines, andmodern software supply chains across enterprise environments. The idealcandidate will have a strong background in **cloud security engineering** ,combined with practical exposure to **AI/ML technologies, AI security risks,and MLSecOps practices** . You will work closely with cloud, engineering,DevOps, and AI/ML teams to implement scalable security controls and supportsecure adoption of AI-enabled solutions. This role alsoincludes supporting software and AI supply chain security initiatives throughmanagement and validation of **SBOM, CBOM, AIBOM, and KBOM** artifacts. **KeyResponsibilities** **1. CloudSecurity Engineering** - Design, implement, and maintain security controls for cloud-native environments and AI/ML workloads. - Secure cloud infrastructure, services, APIs, containers, and workloads across public cloud platforms. - Experience in managing CSPM tools such as Prisma, wiz, orca etc. - Implement and manage: - IAM and least-privilege access controls - Network segmentation and secure connectivity - Encryption and key management - Secrets management and workload isolation - Logging, monitoring, and alerting controls - Conduct cloud security assessments, configuration reviews, and risk analysis. - Support security hardening for cloud-hosted AI services and model-serving infrastructure. **2. AI/MLSecurity** - Support secure deployment and operation of AI/ML systems, including: - LLM-based applications - RAG systems - Model APIs and inference services - Agentic AI workflows - Identify and assess AI-specific security risks such as: - Prompt injection and jailbreak attacks - Model abuse and unauthorized access - Data poisoning and sensitive data leakage - Model inversion and extraction attacks - Implement AI security controls including: - Prompt filtering and validation - Output sanitization - Access restrictions and guardrails - Data protection and context isolation - Participate in AI threat modeling and security design reviews. **3. MLSecOps /DevSecOps** - Integrate security controls into AI/ML and cloud CI/CD pipelines. - Support secure practices for: - Model training and deployment - Container security - Infrastructure as Code (IaC) - Dependency and artifact validation - Implement automated security checks for: - Models and datasets - APIs and infrastructure - Containers and cloud workloads - Assist with secure model versioning, rollback, and deployment validation. **4. Software& AI Supply Chain Security** - Support secure software and AI supply chain initiatives. - Generate, validate, and manage: - **SBOM (Software Bill of Materials)** - **CBOM (Cryptography Bill of Materials)** - **AIBOM (AI Bill of Materials)** - **KBOM (Knowledge Bill of Materials)** - Integrate BOM generation and validation into CI/CD and deployment workflows. - Track dependencies, model provenance, datasets, third-party AI integrations, and cryptographic components. - Support vulnerability management and compliance activities related to software and AI supply chains. **RequiredQualifications** - Bachelors degree in Computer Science, Cybersecurity, Information Security, or related field (or equivalent practical experience). - **47 years of experience** in: - Cloud security engineering - Security operations or security engineering - Application or infrastructure security - Hands-on experience with cloud-native security controls, architectures and CSPM tools. - Understanding of: - IAM, encryption, network security, and secrets management - Secure SDLC and vulnerability management - Containers, APIs, and CI/CD security - Familiarity with AI/ML concepts and AI security risks. - Experience with scripting/programming languages such as: - Python (preferred) - Bash, Go, or JavaScript/TypeScript **PreferredQualifications** - Experience with: - AI/ML platforms and orchestration frameworks - RAG systems, vector databases, and model-serving platforms - Infrastructure as Code (Terraform, CloudFormation, etc.) - Security automation and cloud compliance tooling - Familiarity with: - OWASP Top 10 for LLMs - NIST AI RMF - MITRE ATLAS - MLSecOps and MLOps concepts - Experience working with: - BOM standards and tooling (CycloneDX, SPDX, etc.) - Container and artifact security solutions - Secure software supply chain practices - Relevant cloud or security certifications are a plus. **CoreCompetencies** - Strong analytical and troubleshooting skills - Ability to identify and mitigate cloud and AI security risks - Effective communication and collaboration across technical teams - Strong ownership mindset and attention to detail - Ability to work in fast-paced, engineering-driven environments **What MakesThis Role Unique** This rolecombines **cloud security engineering with modern AI/ML security practices** .You will help secure cloud-native AI systems, protect AI-enabled workloads, andstrengthen software and AI supply chain security through practicalimplementation of controls, automation, and secure engineering practices. Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.