D

Dow Jones

Provides business news, data, and risk

Manager – AI Governance

Security Governance, Risk & ComplianceConfirmed live in the last 24 hours
Full-timeBarcelona, Spain€35k - €55kIn-person

About the Job

Requirements

  • Typically 4–7 years of relevant experience in AI or data engineering, technical AI governance, security architecture, technology risk, model validation, or a related discipline, including practical experience assessing or deploying AI systems.
  • Strong understanding of large language models, retrieval-augmented generation, AI agents, and tool calling, including their limitations and failure modes; familiarity with traditional machine learning and model evaluation is valuable.
  • Ability to review architecture diagrams, API documentation, access policies, configuration files, and logs, and to discuss implementation choices with engineers.
  • Practical proficiency in Python or a comparable scripting language sufficient to inspect integrations, query APIs, analyse results, and prototype control checks or evaluations.
  • Working knowledge of cloud architectures, identity and access management, authentication, secrets management, application security, and data protection.
  • Experience translating risk or policy requirements into implementable controls and assessing evidence of their effectiveness.
  • A degree in Computer Science, Engineering, Data Science, Information Security, or a related discipline, or equivalent practical experience.

Responsibilities

  • Lead technical AI risk assessments by reviewing architectures, data flows, model configurations, integrations, and deployment environments; identify risks, recommend proportionate mitigation, and document residual risks and approval conditions using the Dow Jones AI Risk Matrix.
  • Assess agentic capabilities and system access, including which tools and actions agents can use, whose identity and permissions they use, and their degree of autonomy; evaluate access through MCP, APIs, command-line interfaces, and browser automation, including enterprise-system changes, human approval requirements, action limits, and recovery mechanisms.
  • Evaluate changes to previously approved tools and determine whether AI or agent access introduces new users, permissions, data flows, scale of activity, or autonomy beyond the original approval; reuse existing assessments and focus additional review on material changes.
  • Define and validate technical controls with technical owners, including least-privilege access, credential protection, data-handling restrictions, human oversight, audit logging, and access suspension or revocation mechanisms; review implementation evidence and test results to establish whether controls work as intended.
  • Assess AI-specific security and data risks with Cyber Security and Privacy, including prompt injection, unintended disclosure, inappropriate tool use, and risks introduced by external models, connectors, and dependencies; evaluate how sensitive information, proprietary content, and personal data enter model context, retrieval systems, outputs, and logs.
  • Establish AI evaluation and monitoring requirements, including proportionate tests for accuracy, groundedness, reliability, bias, and safe behaviour, including tool selection and execution for agents; work with delivery teams to set acceptance criteria and monitor failures, control effectiveness, and changes in system behaviour.
  • Build scalable governance processes by developing technical standards, assessment templates, and approved integration patterns, and establishing routes for routine approvals, exceptions, and reassessment when models, tools, permissions, or intended uses change.
  • Conduct technical vendor assessments and support pilots by examining vendor architecture, data handling, access controls, evaluation evidence, and monitoring capabilities; define risk and performance criteria for proofs of concept and assess readiness for production use.
  • Support governance throughout the AI life cycle by maintaining visibility into system owners, risk assessments, dependencies, approval conditions, and outstanding mitigation; contribute to incident reviews and ensure lessons inform future controls and assessments.
  • Provide technical advice by presenting findings and recommendations to the AI Steering Committee and other decision-makers, translating policy and regulatory requirements into technical guidance with Legal and Privacy, and contributing targeted training for teams building or deploying AI.

Desired Qualifications

  • Assessing agentic workflows, MCP integrations, or AI access to enterprise platforms.
  • Designing AI evaluations, adversarial testing, or production monitoring.
  • Applying AI governance frameworks and translating requirements such as the EU AI Act into technical controls.
  • Working with sensitive information, proprietary content, or intellectual property in media, publishing, or other complex enterprise environments.

About the Company

Dow Jones

Provides business news, data, and risk

Dow Jones provides business news, financial information, and data tools for financial firms, professionals, and investors around the world. Its offerings include the Wall Street Journal, Dow Jones Newswires, and Factiva, which supply breaking news, exclusive insights, and large data sets. It also offers risk and compliance solutions to help organizations manage anti-money laundering, anti-corruption, and economic sanctions. The company's revenue comes from subscriptions, data licensing, and advertising. By combining trusted media with extensive data resources, Dow Jones helps customers stay informed and make better decisions in finance and business.

Company size
5,001-10,000
Company stage
Acquired
Total funding
Not listed
Headquarters
New York City, New York
Founded
1881

Recently Posted Jobs

Explore more opportunities at Dow Jones

See more jobs