ERP Strategic Advisor

3 months ago

Bengaluru Karnataka, India NTT DATA Full time

**Job Summary**:
**Key Responsibilities**:

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

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