Expert AI & Data Governance

Volkswagen Group

Puebla de Zaragoza

Hybrid

MXN 900,000 - 1,300,000

Full time

2 days ago

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Job summary

Audi México in San José Chiapa, MX, is seeking a governance lead to establish and operate an integrated AI and Data Governance framework across the lifecycle of data products, models, and AI solutions. You will drive risk-based control mechanisms and ensure alignment with regulatory and internal requirements.

The role collaborates with IT, Data Science, Information Security, Legal, and Procurement to scale responsible AI use while maintaining compliance and enabling innovation.

Qualifications

University degree in Computer Science, Data Science, Business Informatics, or a comparable field.
Advanced English Level.
Professional experience in AI/ML, Data Governance, Technology Risk, Compliance, Data Privacy, Information Security, Audit, or Enterprise Architecture.
Strong understanding of AI/ML lifecycle from data ingestion to deployment, monitoring, and decommissioning.
Practical experience in data quality, metadata management, data catalogs, data lineage, data classification, access control, and data lifecycle management.
Knowledge of EU AI Act, GDPR, and interfaces with product safety, cybersecurity, copyright, and supplier management.
Knowledge of ISO/IEC 42001, ISO/IEC 23894, ISO/IEC 27001, NIST AI RMF, and DAMA-DMBOK data-management practices.
Experience with assessments, control frameworks, policies, process design, audit evidence, and remediation management.

Responsibilities

Develop, maintain, and operationalize the Group-wide AI & Data Governance framework, including policies, standards, roles, decision-making bodies, and control mechanisms.
Operate a central inventory for AI systems, models, and relevant data products with documented purpose, owners, data sources, risk classification, lifecycle status, and evidence.
Conduct and facilitate intake, classification, and risk-assessment processes for new or materially changed AI use cases.
Assess data provenance, data quality, representativeness, data approvals, usage rights, consent, retention, deletion, and lineage for training, validation, testing, RAG, and inference.
Define and review required artifacts such as Model Cards, Data Cards, AI Impact Assessments, Data Protection Impact Assessments, technical documentation, human-oversight concepts, test evidence, and approval decisions.
Integrate AI Governance into existing processes for Data Governance, Data Privacy, Information Security, Architecture, Procurement, Legal Compliance, supplier management, and the internal control system.
Advise Product Owners, Data Owners, Data Stewards, architects, Data Scientists, and engineering teams on implementing Responsible AI and Data Governance requirements.
Assess external models, data sources, cloud/SaaS services, and AI suppliers, including contractual, data, security, transparency, and exit requirements.
Plan and support control testing, internal audits, management reviews, and remediation tracking for findings and exceptions.
Develop role-based qualification and communication formats for AI literacy, governance processes, and responsible data use.
Prepare decision papers and management reporting on portfolio, risks, exceptions, actions, maturity, and governance effectiveness.
Monitor relevant regulatory, standards-related, and technological developments and translate them into concrete change requirements.

Skills

Problem Solving

Customer Service

Technical Support

Communication Skills

Troubleshooting

Conflict Management

OS Configuration

Programming Languages

Data Backup

Analytical Thinking

Cybersecurity

Scripting

Innovative Thinking

Network Configuration

Education

Bachelor's degree in Computer Science / Data Science / Business Informatics

Job description

The position establishes and operates an integrated governance framework for data and AI. It translates regulatory, ethical, security-related, and internal requirements into practical processes, controls, and evidence across the entire lifecycle of data products, machine-learning models, generative AI solutions, and agentic systems.

The role creates reliable decision-making foundations for business functions, IT, Data Science, Information Security, Data Privacy, Legal, Procurement, and Internal Audit. The objective is not to slow innovation, but to identify risks early, clarify accountabilities, and safely scale AI use cases from concept to operation.

Possible Tasks within this Role

Develop, maintain, and operationalize the Group-wide AI & Data Governance framework, including policies, standards, roles, decision-making bodies, and control mechanisms.
Operate a central inventory for AI systems, models, and relevant data products with documented purpose, owners, data sources, risk classification, lifecycle status, and evidence.
Conduct and facilitate intake, classification, and risk-assessment processes for new or materially changed AI use cases.
Assess data provenance, data quality, representativeness, data approvals, usage rights, consent, retention, deletion, and lineage for training, validation, testing, RAG, and inference.
Define and review required artifacts such as Model Cards, Data Cards, AI Impact Assessments, Data Protection Impact Assessments, technical documentation, human-oversight concepts, test evidence, and approval decisions.
Integrate AI Governance into existing processes for Data Governance, Data Privacy, Information Security, Architecture, Procurement, Legal Compliance, supplier management, and the internal control system.
Advise Product Owners, Data Owners, Data Stewards, architects, Data Scientists, and engineering teams on implementing Responsible AI and Data Governance requirements.
Assess external models, data sources, cloud/SaaS services, and AI suppliers, including contractual, data, security, transparency, and exit requirements.
Plan and support control testing, internal audits, management reviews, and remediation tracking for findings and exceptions.
Develop role-based qualification and communication formats for AI literacy, governance processes, and responsible data use.
Prepare decision papers and management reporting on portfolio, risks, exceptions, actions, maturity, and governance effectiveness.
Monitor relevant regulatory, standards-related, and technological developments and translate them into concrete change requirements.

Qualification requirements

University degree in Computer Science, Data Science, Business Informatics, or a comparable field.
Advanced English Level.
Professional experience in at least two of the following areas: AI/ML, Data Governance, Technology Risk, Compliance, Data Privacy, Information Security, Audit, or Enterprise Architecture.
Strong understanding of the AI/ML lifecycle, from data ingestion and feature engineering through training/fine-tuning and RAG to deployment, monitoring, and decommissioning.
Practical experience in data quality, metadata management, data catalogs, data lineage, data classification, access control, and data lifecycle management.
Knowledge of the EU AI Act, GDPR, and relevant interfaces with product safety, cybersecurity, copyright, and supplier management.
Knowledge of recognized frameworks and standards, particularly ISO/IEC 42001, ISO/IEC 23894, ISO/IEC 27001, NIST AI RMF, and data-management practices based on DAMA-DMBOK.
Experience with assessments, control frameworks, policies, process design, audit evidence, and remediation management.

Skills