1. Strategy and Leadership 

• Develop and lead the company’s overarching Responsible AI (RAI) strategy, ensuring alignment with business objectives and societal expectations. 

• Provide expert advice to executive leadership on emerging risks, trends, and opportunities in Responsible AI. 

• Drive a culture of ethical AI awareness across the organization through training, workshops, and communication. 

2. AI Governance and Compliance 

• Establish and implement governance frameworks for AI/ML development and deployment, ensuring alignment with global regulatory and industry standards. 

• Define and enforce policies for fairness, transparency, accountability, and privacy in AI solutions. 

• Conduct regular audits and assessments of AI systems to identify and mitigate ethical, social, and legal risks. 

• Develop guidelines and tools for explainable AI to enhance trust and understanding of AI systems. 

• Collaborate with legal and compliance teams to ensure adherence to AI-related regulatory requirements, such as GDPR and other global privacy laws. 

3. Risk Assessment and Mitigation 

• Identify potential risks in AI/ML systems, including biases, privacy issues, and unintended consequences. 

• Design and implement risk assessment protocols to proactively address issues before deployment. 

• Work with technical teams to improve robustness and resilience of AI systems against adversarial attacks. 

• Ensure AI models are interpretable and accessible to stakeholders, enhancing their accountability and usability. 

• Develop incident response plans for AI-related failures or ethical concerns. 

4. Collaboration and Stakeholder Engagement 

• Partner with AI engineering, product, and business teams to embed responsible AI principles into the entire development lifecycle. 

• Collaborate with external organizations, academia, and industry bodies to stay ahead of emerging trends and best practices in Responsible AI. 

• Act as a bridge between technical and non-technical teams, ensuring responsible AI principles are well understood and implemented. 

• Build and maintain relationships with external audit and certification bodies for responsible AI. 

• Advocate for the organization’s Responsible AI initiatives through strategic partnerships and community engagement. 

5. Innovation and Continuous Improvement 

• Stay abreast of the latest research and innovations in ethical AI, fairness, and governance. 

• Promote the adoption of state-of-the-art tools, techniques, and methodologies for responsible AI. 

• Drive innovation by encouraging cross-disciplinary research and exploration of new approaches to ethical AI. 

• Monitor and evaluate the effectiveness of Responsible AI programs, iterating to address gaps and improve outcomes. 

• Publish research papers, case studies, and white papers to establish the company as a leader in Responsible AI. 

Qualifications & Experiences: 

Academic Qualifications: 

• Master’s or Ph.D. in Computer Science, Data Science, Ethics, Law, or a related field, with a focus on AI/ML, ethics, or governance. 

• Certifications or specialized training in Responsible AI, AI ethics, or governance frameworks are highly desirable. 

Professional Experience: 

• 8+ years of experience in AI/ML, with at least 3+ years focused on ethical AI, governance, or risk management. 

• Proven track record in developing and implementing AI governance frameworks Official notification