AI Security Engineer

Overview

AI Tool & Vendor Security Review

• Review AI tools, AI vendors, and AI-enabled SaaS applications before approval for company use
• Conduct security and risk assessments for third-party AI solutions
• Evaluate vendor security posture and data handling practices
• Ensure AI tools comply with company security policies and data protection standards
• Maintain and update an inventory of AI tools and AI integrations used across the organization

AI Application Security

• Assess AI-powered applications and AI-enabled workflows for security risks
• Review AI connectors, plugins, APIs, and integrations used by internal applications
• Evaluate security risks in AI-generated or AI-assisted code
• Implement Security Controls for AI Solutions
• Provide guidance to engineering teams on secure AI integration practices
• Review prompt templates and AI workflows to prevent prompt injection or sensitive data exposure

• AI Risk Assessment & Threat Modelling

• Perform threat modelling for AI-enabled applications and automated workflows
• Identify risks including
• Prompt injection attacks
• Sensitive data leakage
• Insecure AI integrations
• Unauthorized access to AI systems
• Misuse of AI-generated outputs
• Recommend appropriate mitigation strategies and security control.

Data Protection & AI Governance

• Ensure sensitive data is not exposed to AI tools in violation of company data protection policies
• Define best practices for safe employee usage of AI tools
• Support implementation of internal AI usage policies and governance frameworks

• AI Security Monitoring & Incident Response

• Monitor AI tool usage patterns to detect abnormal or potentially risky activity
• Support investigation and response for security incidents involving AI tools or AI integrations
• Identify threats related to AI technologies and recommend mitigation actions

Security Framework Alignment

• Align AI security practices with recognized frameworks such as:

• NIST AI Risk Management Framework

• OWASP Top 10 for LLM Applications

• ISO/IEC 42001 AI Management System

• Support documentation and evidence preparation for audits or compliance reviews related to AI usage.

🧙‍♂️ The Magic You Bring

• 2–4 years of experience in Cyber Security, Security Engineering, or Security Operations.
• Experience reviewing applications, SaaS tools, or vendors from a security perspective.

Basic Understanding Of

Encryption

• Logging and monitoring
• Familiarity with cloud platforms such as AWS and GCP.
• Ability to identify security risks in AI tools or AI-generated applications.
• Good communication and documentation skills
• Exposure to AI governance concepts (acceptable use, tool inventories, data classifications) even if informal
• Experience partnering with Legal/Privacy or Compliance on control mapping/evidence.
• Understanding of AI and Large Language Model (LLM) architectures
• Exposure to AI governance concepts including AI acceptable use policies and tool inventories
• Experience working with Legal, Privacy, or Compliance teams on control reviews
• Experience supporting secure development practices or reviewing application code

Inside Snoonu’s Universe

The Dream We’re Chasing

The Quest We’re On

👥 Be Customer Obsessed

👨‍💼 It's All About People

Perks & Worklife Magic At Snoonu

Builder’s Playground

Flexible Time Off

Agile Everything

Great Place to Work® Certified

Beyond the Code: Giving Back Matters

Diversity Isn’t Just a Buzzword

Let’s Build the Future Together