Back
Senior niche AI assurance role but strong Unilever brand and Bangalore metro increases candidate competition.
Specialized responsible AI, red-teaming, and regulatory expertise limits cross-industry transferability.
Explicit 10-year requirement plus mandated AI risk, regulatory and assurance expertise makes filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Own AI Technical Risk Assurance across Unilever’s AI systems, including ML, Generative AI, and agentic systems, ensuring they are safe, fair, robust, and compliant before deployment and during operations.
Lead AI red teaming by designing and executing adversarial testing simulating real-world misuse to identify risks and validate AI system robustness.
Manage end-to-end AI risk assurance including risk assessments, continuous monitoring, evidence management, and cross-functional coordination with Privacy, Cyber, Legal, and others to embed assurance controls.
10 years of experience in AI/ML risk, model governance, technical audit, information security, or closely related fields in complex large-scale environments.
Strong understanding of AI and ML architectures, including large language models, generative AI, and agentic systems with knowledge of their failure modes and bias vectors.
Familiarity with AI red teaming methodologies and understanding of regulatory frameworks such as the EU AI Act, GDPR, NIST AI RMF, and ISO 42001.
Work Experience Required: 10 years in relevant domains as stated; Notice Period: Not explicitly mentioned in the JD.
Experienced in operating technical AI risk assurance in large-scale, complex, and fast-evolving AI environments with a strategic mindset towards responsible AI deployment.
Capable of translating complex technical AI risk findings into clear, executive-level insights and influencing stakeholders across functions without formal authority.
Automation-first and evidence-focused approach to designing scalable assurance processes that embed risk control early and continuously in AI lifecycle.