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 :

1. 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 :

1. IAM and least-privilege access controls

2. Network segmentation and secure connectivity

3. Encryption and key management

4. Secrets management and workload isolation

5. 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/ML Security :

Support secure deployment and operation of AI/ML systems, including :

1. LLM-based applications

2. RAG systems

3. Model APIs and inference services

4. Agentic AI workflows

Identify and assess AI-specific security risks such as :

1. Prompt injection and jailbreak attacks

2. Model abuse and unauthorized access

3. Data poisoning and sensitive data leakage

4. Model inversion and extraction attacks

Implement AI security controls including :

1. Prompt filtering and validation

2. Output sanitization

3. Access restrictions and guardrails

4. 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 :

1. Model training and deployment

2. Container security

3. Infrastructure as Code (IaC)

4. Dependency and artifact validation

Implement automated security checks for :

1. Models and datasets

2. APIs and infrastructure

3. 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 :

1. SBOM (Software Bill of Materials)

2. CBOM (Cryptography Bill of Materials)

3. AIBOM (AI Bill of Materials)

4. 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 :

- Bachelors degree in Computer Science, Cybersecurity, Information Security, or related field (or equivalent practical experience).

47 years of experience in :

1. Cloud security engineering

2. Security operations or security engineering

3. Application or infrastructure security

- Hands-on experience with cloud-native security controls, architectures and CSPM tools.

Understanding of :

1. IAM, encryption, network security, and secrets management

2. Secure SDLC and vulnerability management

3. Containers, APIs, and CI/CD security

- Familiarity with AI/ML concepts and AI security risks.

Experience with scripting/programming languages such as :

1. Python (preferred)

2. Bash, Go, or JavaScript/TypeScript

Preferred Qualifications:

Experience with :

1. AI/ML platforms and orchestration frameworks

2. RAG systems, vector databases, and model-serving platforms

3. Infrastructure as Code (Terraform, CloudFormation, etc.)

4. Security automation and cloud compliance tooling

Familiarity with :

1. OWASP Top 10 for LLMs

2. NIST AI RMF

3. MITRE ATLAS

4. MLSecOps and MLOps concepts

Experience working with :

1. BOM standards and tooling (CycloneDX, SPDX, etc.)

2. Container and artifact security solutions

3. 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.