AI Security Engineer

Job Title: AI Security Engineer

Role Overview

We are seeking a skilled AI Security Engineer to help design, implement, and maintain secure cloud-native AI platforms and applications. This role focuses on securing AI/ML workloads, cloud infrastructure, APIs, data pipelines, and modern software supply chains across enterprise environments.

The ideal candidate 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 support secure adoption of AI-enabled solutions.

This role also includes supporting software and AI supply chain security initiatives through management and validation of SBOM, CBOM, AIBOM, and KBOM artifacts.

Key Responsibilities

Cloud Security 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.

AI/ML Security

• 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.

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.

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.

Required Qualifications

• Bachelor's degree in Computer Science, Cybersecurity, Information Security, or related field (or equivalent practical experience).
• 4–7 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

Preferred Qualifications

• 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.

Core Competencies

• 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 Makes This Role Unique

This role combines cloud security engineering with modern AI/ML security practices. You will help secure cloud-native AI systems, protect AI-enabled workloads, and strengthen software and AI supply chain security through practical implementation of controls, automation, and secure engineering practices.