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
- Solid 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.

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