Senior AI Security Engineer

Job Summary

We are seeking an experienced Senior AI Security Engineer to design, implement, and strengthen security controls for AI-powered applications, machine learning platforms, and Generative AI solutions. The ideal candidate will have strong expertise in application security, cloud security, AI/ML security, and threat modeling, with hands-on experience identifying and mitigating security risks across the AI lifecycle.

Key Responsibilities

• Design and implement security controls for AI/ML systems, LLM-powered applications, and Generative AI platforms.
• Conduct threat modeling, security assessments, and penetration testing for AI applications and APIs.
• Identify and mitigate AI-specific threats, including prompt injection, data poisoning, model extraction, sensitive data leakage, and insecure model integrations.
• Secure LLM applications, RAG pipelines, vector databases, AI agents, and model-serving infrastructure.
• Implement identity and access management, encryption, secrets management, and data protection controls.
• Integrate security testing and automated vulnerability scanning into CI/CD pipelines and MLOps workflows.
• Establish security guardrails, monitoring, logging, and incident response procedures for AI workloads.
• Collaborate with AI/ML engineers, cloud architects, DevSecOps teams, and compliance stakeholders to embed security throughout the development lifecycle.
• Evaluate AI security tools, frameworks, and emerging threats, and recommend appropriate mitigation strategies.
• Support security governance and compliance initiatives aligned with organizational policies and industry standards.

Required Skills and Qualifications

• 8+ years of experience in cybersecurity, application security, cloud security, or product security.
• Strong understanding of AI/ML security risks, LLM vulnerabilities, and Generative AI security best practices.
• Hands-on experience securing Python-based applications, REST APIs, microservices, and AI integrations.
• Knowledge of AWS, Azure, or GCP security services and cloud-native security architecture.
• Experience with IAM, OAuth 2.0, OIDC, encryption, secrets management, and network security.
• Familiarity with DevSecOps, CI/CD pipelines, container security, Kubernetes, and infrastructure as code.
• Understanding of OWASP Top 10, OWASP Top 10 for LLM Applications, MITRE ATLAS, and NIST AI Risk Management Framework.
• Experience with vulnerability management, security testing, incident response, and risk assessment.

Preferred Qualifications

• Experience securing enterprise-grade LLM applications, AI agents, and Retrieval-Augmented Generation (RAG) systems.
• Familiarity with AI red teaming, adversarial machine learning, model evaluation, and guardrail implementation.
• Knowledge of AI governance, privacy engineering, and responsible AI practices.
• Relevant security certifications such as CISSP, CCSP, CSSLP, or cloud security certifications are a plus.

Key Competencies

• Strong analytical and problem-solving skills.
• Ability to translate complex AI security risks into practical technical controls.
• Excellent communication and cross-functional collaboration skills.
• Ability to work independently in a fast-evolving AI security environment.