ERP Strategic Advisor

Job Summary:

We are seeking a highly skilled and motivated AI/ML Application Security Analyst with expertise in MLSecOps and large language models (LLMs) to join our team. The ideal candidate will possess a deep understanding of AI/ML technologies, security best practices, and the unique challenges associated with LLMs. This role involves securing AI/ML applications and systems throughout their lifecycle, from development to deployment, ensuring the integrity, confidentiality, and availability of data and models.

Key Responsibilities:

- Conduct security assessments and audits of AI/ML applications, including LLMs, to identify vulnerabilities and risks.

- Develop and implement security measures and protocols tailored for AI/ML systems and LLMs, including secure coding practices, data protection, and model integrity.

- Monitor AI/ML applications for security breaches, perform incident response, and implement remediation strategies.

- Collaborate with data scientists, machine learning engineers, and IT teams to integrate security into the AI/ML development and deployment lifecycle (MLSecOps).

- Stay abreast of the latest security threats, vulnerabilities, and advancements in AI/ML security, with a focus on LLMs.

- Create and maintain comprehensive documentation for security policies, procedures, and incident reports.

- Provide security training and awareness programs for AI/ML development teams to promote best practices.

- Evaluate third-party AI/ML solutions and services for security compliance and risk management.

- Implement adversarial testing and robustness evaluation to defend against attacks on AI/ML models, particularly LLMs.

Required Qualifications:

- Bachelor’s degree in Computer Science, Information Security, Data Science, or a related field.

- Proven experience in application security with a focus on AI/ML systems, MLSecOps practices, and large language models.

- In-depth knowledge of AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and LLM platforms.

- Familiarity with secure coding practices, vulnerability management, and threat modeling.

- Strong understanding of data protection and privacy regulations (e.g., GDPR, CCPA).

- Hands-on experience with security tools and technologies (e.g., SIEM, IDS/IPS, encryption, authentication mechanisms).

- Excellent analytical and problem-solving skills, with a keen attention to detail.

- Strong communication skills and ability to work collaboratively in a cross-functional team environment.

Preferred Qualifications:

- Master’s degree in a relevant field.

- Industry certifications such as CISSP, CEH, OSCP, or specific AI/ML certifications.

- Experience with cloud security, particularly in AWS, Azure, or Google Cloud environments.

- Knowledge of adversarial machine learning, model robustness, and techniques to defend against such threats.

- Familiarity with MLOps practices and secure deployment methods for AI/ML models.

- Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes).

- Specific experience with securing LLMs and understanding of their unique security challenges.