Responsible AI, AI Risk & Security Lead

We’re building AI capabilities that will transform one of the world’s largest industrial organizations from intelligent operations to next-generation industrial solutions.

Be part of this exciting journey where AI, Agentic AI, Data, Cloud, and innovation meet real-world impact at a global scale.

What makes this opportunity unique is the scale, complexity, and impact.

You will have the opportunity to:

• Build AI products and solutions that operate across a truly global enterprise.
• Work at the intersection of industry, engineering, business transformation, and technology.
• Collaborate with leading experts from ArcelorMittal and strategic technology partners.
• Help establish standards, platforms, governance, and operating models that will shape our future AI landscape.
• Convert bold ideas into production-grade solutions that create measurable business value.
• Contribute to one of the most ambitious AI transformation programs currently underway in the industrial sector.

We’re looking for passionate AI Engineers, Data Specialists, Architects, Cloud Engineers, and technology innovators who want to solve complex challenges, build solutions from the ground up, and shape what comes next.

🔥 Ready to take your AI career to the next level? Explore our open positions and apply now on LinkedIn. Come build the future of Industrial AI with ArcelorMittal!

Job Title – Responsible AI, AI Risk & Security Lead

Job Nature – Permanent

Work Location – Hyderabad

Experience – 12+ years across Data, AI, Risk or Cybersecurity; 7+ years in risk, compliance, data protection, security architecture or AI governance; 3+ years on Azure security; and 2+ years applied to AI, generative AI or agentic systems.

Purpose of the Role

Establish and operate ArcelorMittal’s integrated Responsible AI, AI risk and AI security governance for every AI use case and shared platform service. The role owns risk classification, impact assessments, human-oversight design, security architecture, threat modelling, evidence requirements, regulatory alignment, approval pathways and post-deployment assurance. The implementation partner prepares evidence and recommends; this role ensures ArcelorMittal can make informed risk and release decisions.

Key Responsibilities

• Classify each use case by impact, autonomy, data sensitivity, user population and foreseeable harm using Low /Medium / High risk tiers and record the decision in the Use Case Charter.
• Define Responsible AI and security requirements for impact assessment, transparency, human oversight, contestability, testing, identity, secrets, network isolation, data protection, APIs, agent runtimes and operations.
• Review agent actions, model limitations, evaluation plans, threat models, failure modes, tool permissions and human-in-the-loop design before design sign-off and production authorization.
• Maintain Responsible AI and security decisions, conditions, findings, residual risks and approval status; escalate risk to accountable ArcelorMittal authorities.
• Ensure alignment with the EU AI Act, GDPR, ArcelorMittal Responsible AI and security standards, ISO 42001, ISO 27001, NIST guidance and works-council requirements.
• Set threat-modelling, red-teaming, control-evidence, security-testing and release-readiness expectations; require remediation where exposure is unacceptable.
• Define AI-specific monitoring and incident triggers for harm, drift, misuse, prompt injection, data exfiltration and control failure, integrated with Security Operations.
• Track systemic findings, maintain the Responsible AI and security pattern library, and prioritize reusable remediation and control improvements.
• Coach business owners, reviewers and engineering teams; operate integrated stage gates across Intake, Experimentation Pods, the AI Platform and Solution Pods.

Preferred Skills

• Stakeholder orientation and executive communication
• Results orientation and pragmatic risk judgement
• Courage to challenge and independent assurance
• Decision making and structured documentation
• Cross-functional and cross-cultural collaboration
• Innovation, learning agility and systems thinking
• Capability building and knowledge transfer

Good to have skills

• Responsible AI frameworks, EU AI Act, NIST AI RMF and ISO/IEC 42001
• AI impact assessment, human oversight, evaluation, red-teaming and lifecycle governance
• Azure security architecture, threat modelling and secure design r…