About the role

Job Description: Responsible and Secure AI Governance Specialist

We are seeking a highly motivated Responsible and Secure AI Governance Specialist to join our Cyber team. The ideal candidate will be engaged in the design, implementation, and monitoring of governance frameworks that ensure the ethical, secure, and compliant deployment of AI technologies within our services. This role will collaborate closely with technology, security, compliance, legal, and business units to manage AI risks, uphold data privacy, and align AI systems with evolving regulatory standards.

Responsibilities:

Develop, implement, and maintain AI governance policies, standards, and best practices tailored for ITES environments.
Conduct AI risk assessments focused on model bias, fairness, security vulnerabilities, and compliance with data privacy laws (GDPR, HIPAA, etc.).
Collaborate cross-functionally to embed security and ethical considerations into the AI/ML lifecycle, including data acquisition, model development, testing, deployment, and monitoring.
Design and oversee continuous AI model monitoring processes to detect anomalies, bias, data drift, and security threats.
Support incident response planning for AI-related security breaches or compliance issues.
Provide training and awareness sessions on AI governance, ethics, and security best practices for internal teams.
Stay current with AI governance frameworks, regulations, and emerging risks; advise leadership on necessary policy updates and strategic initiatives.
Work with Technology and cloud teams to ensure AI systems align with organizational cybersecurity and data protection policies.
Prepare reports and dashboards for leadership to highlight AI governance metrics and compliance status.
Research on AI regulations and ensure program alignment.

Subject Matter Expertise:

Proficiency in data privacy and cybersecurity best practices related to AI systems.
Experience with cloud AI platforms (AWS SageMaker, Azure AI, Google AI).
Familiarity with AI ethics frameworks (e.g., NIST AI RMF, OECD AI Principles, EU AI Act).
Knowledge of programming languages used in AI/ML (Python, R).
Knowledge of AI governance platforms (e.g. Credo.ai, IBM's AI Fairness 360, Priva Sapien) and Certifications such as CISSP, CDPSE, or AI Governance-related credentials are a plus.
Strong understanding of AI/ML technologies and development lifecycle.
Knowledge of regulatory frameworks impacting AI and data (e.g., GDPR, HIPAA, CCPA).
Hands-on experience with AI monitoring tools or platforms that support model auditing and anomaly detection.
Familiarity with AI fairness, bias mitigation, explainability, and robustness assessment techniques.

Thought Leadership:

Provide thought leadership to fellow team members across business and technical project dimensions solving complex business requirements.
Demonstrate forward thinking around where the organization is going and how technology can support these efforts.
Advocate and define security architecture vision from a strategic perspective, including internal and external platforms, tools and systems.

Cross-Functional and Collaboration:

Drive scope definition, requirements analysis, functional and technical design, product configuration, and production deployment.
Ensure delivered solutions meet/perform to technical and functional/non-functional requirements.
Provide technical expertise and ownership in the diagnosis and resolution of an issue, including the determination and provision of a workaround solution or escalation to service owners.
Ensure delivered solutions are realized in the time frame committed; work in conjunction with project sponsors to size and manage scope and risk.
Provide support and technical governance, expertise related to cloud architectures, deployment, and operations.

Mentoring:

Act as the coach and mentor to team members and technical staff on their assigned project tasks.
Lead the definition and development of cloud reference architecture and management systems.
Conduct project reviews with team members.

Requisites:

Bachelor's degree in computer science, computer engineering, information technology, or relevant field.
Overall experience 12+ years with proven experience (3+ years) in AI governance, AI risk management, or AI security, preferably in ITES or technology-driven environments.
Positive attitude and a strong commitment to delivering quality work.
Effective communication skills (written and verbal) to properly articulate complicated cloud architecture and reports to management.
Excellent analytical, problem-solving, and communication skills.