Job Title: AI Governance Lead

Experience: 12+ years

Location: Bangalore, Pune, Hyderabad

Domain: Banking

Notice Period: Immediate to 45 days

Job Description:

A senior AI leader who can combine AI governance, risk management, regulation, security, compliance, and business consulting expertise to establish trusted, scalable, and enterprise-grade AI adoption programs for global customers while positioning as a leader in Responsible and Agentic AI governance

This role demands thought leadership, strong stakeholder management capabilities, consulting expertise, and the ability to drive governance initiatives across large-scale AI transformation programs.

Skills & Experience

AI Governance Skills

- 12+ years of experience in Enterprise IT, Data, Security, Risk, Compliance, and AI, with at least 5 years focused on AI Governance, Responsible AI, Model Risk Management, and AI Compliance.
- Strong understanding of AI/ML lifecycle governance frameworks and model management practices.
- Experience establishing AI Governance Councils, operating models, governance boards, and policy frameworks.
- Expertise in AI risk assessment methodologies and control frameworks.
- Practical experience developing governance standards for Generative AI and Agentic AI systems.
- Strong knowledge of AI regulations and standards, including:
- EU AI Act
- NIST AI Risk Management Framework
- ISO/IEC 42001
- ISO 27001
- SOC 2
- GDPR
- HIPAA
- Industry-specific compliance frameworks

- Experience in AI model inventory management, model validation, monitoring, and lifecycle controls.
- Understanding of AI explainability, transparency, fairness, bias detection, and accountability principles.
- Knowledge of cybersecurity controls applicable to AI systems, including data protection, prompt security, model security, and AI supply chain risk management.
- Experience in governance of LLMs, foundation models, RAG architectures, AI agents, and multimodal AI systems.

AI & GenAI Skills

- Strong understanding of Generative AI concepts including:
- LLMs
- Embeddings
- Vector Databases
- RAG
- Fine Tuning
- Agentic Systems
- Multi-Agent Platforms

- Deep knowledge of AI safety, alignment, guardrails, content moderation, and responsible AI controls.
- Experience implementing governance controls around:

- Prompt Management
- Model Selection
- AI Output Validation
- Human-in-the-Loop Systems
- AI Monitoring
- Explainability Frameworks

- Familiarity with enterprise AI platforms such as:

- Azure AI Foundry
- Azure OpenAI
- Google Vertex AI
- AWS Bedrock
- Databricks
- NVIDIA AI Enterprise
- Open-source AI ecosystems

Risk & Compliance Skills

- Experience performing enterprise AI risk assessments.
- Strong understanding of operational, reputational,regulatory, ethical,



and security risks associated with AI.
- Experience creating AI control frameworks and audit mechanisms.
- Ability to define governance KPIs, control monitoring dashboards, and compliance scorecards.
- Experience supporting internal and external audits for AI and data governance programs.

Consulting & Leadership Skills

- Experience advising CXOs and senior business leaders on AI governance strategies.
- Strong communication and executive presentation skills.
- Experience leading large-scale governance transformation initiatives.
- Ability to influence cross-functional stakeholders globally.
- Expertise in governance-related due diligence, assessments, and maturity evaluations.

Roles & Responsibilities

This role requires strong leadership to drive enterprise-wide AI governance initiatives and position Tech Mahindra as a trusted advisor in Responsible AI and AI Risk Management.

Key responsibilities include:

Governance Strategy & Framework Development

- Define and implement enterprise AI governance frameworks, operating models, and policies.
- Establish governance practices covering AI lifecycle management, risk management, compliance, security, and ethics.
- Build governance standards for Generative AI, Agentic AI, ML, and automation initiatives.
- Develop governance maturity models and adoption roadmaps.

Responsible AI & Trustworthy AI

- Establish Responsible AI principles, controls, and operational processes.
- Define policies for fairness, transparency, explainability, privacy, accountability, and human oversight.
- Review AI solutions to ensure responsible AI compliance before deployment.
- Drive AI ethics reviews and governance board approvals where required.

Risk Management & Compliance

- Lead AI risk assessments across internal and client AI initiatives.
- Identify and mitigate operational, compliance, regulatory, security, and ethical risks.
- Monitor emerging regulations and ensure governance programs remain compliant.
- Define controls for model governance, auditability, traceability, and documentation.

AI Security Governance

- Collaborate with cybersecurity teams to establish AI security controls.
- Define governance standards for:
- Prompt Security
- Model Security
- Data Security
- AI Agent Governance
- Third-Party Model Governance

- Assess AI platform security posture and compliance readiness.





AI Lifecycle Governance

- Define standards for:
- Model Development
- Model Validation
- Deployment Approval
- Monitoring
- Retirement

- Establish enterprise model registries and governance workflows.
- Ensure appropriate controls exist across AI and GenAI development pipelines.

Client Advisory & Consulting

- Act as a trusted advisor to clients on AI governance, compliance, and responsible AI adoption.
- Conduct AI governance assessments and due diligence workshops.
- Present findings, recommendations, and governance roadmaps to executive stakeholders.
- Support AI solution reviews from governance and compliance perspectives.

Governance Operating Model

- Establish AI Governance Councils and oversight mechanisms.
- Coordinate with Legal, Compliance, Security, Privacy, Risk, and Business teams.
- Create governance reporting frameworks and executive dashboards.
- Drive governance awareness and AI policy adoption programmes.

Industry Leadership

- Represent Tech Mahindra at industry forums, analyst discussions, and governance working groups.
- Contribute to thought leadership, whitepapers, governance methodologies, and client collateral.
- Monitor emerging trends in AI regulation, governance technologies, and best practices.

Due Diligence & Assessment

- Assess client AI ecosystems, governance maturity, and regulatory readiness.
- Evaluate AI operating models, policies, controls, and governance structures.
- Analyze AI solution pipelines for governance gaps and risk exposures.
- Conduct Responsible AI maturity assessments.
- Develop governance transformation roadmaps and implementation recommendations.
- Create executive-level reports highlighting governance risks, opportunities, compliance posture, and remediation actions.

Collaboration & Communication

- Work closely with AI Architects, Data Scientists, Security Architects, Legal Teams, Compliance Officers, and Business Leaders.
- Communicate governance requirements clearly across technical and business stakeholders.
- Facilitate governance reviews, steering committees, and executive governance boards.
- Maintain governance artifacts, policies, standards, controls, and operational documentation.

Preferred Certifications

- ISO/IEC 42001 Lead Implementer or Lead Auditor
- NIST AI Risk Management Framework Certifications
- Certified Information Systems Security Skilled (CISSP)
- Certified Information Security Manager (CISM)
- Certified Data Privacy Solutions Engineer (CDPSE)
- Certified in Risk and Information Systems Control (CRISC)
- Microsoft Certified: Azure AI Engineer Associate
- Google Cloud Professional ML Engineer
- Responsible AI Certifications from recognized institutions

📌 AI Governance Lead (Hyderabad)
🏢 Tech Mahindra
📍 Hyderabad