Why Keyrus, Why Now!

Keyrus is an international group of 2,800 consultants and experts across 28 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.

For more than 30 years, we have been building the data foundations that make intelligent systems work — designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalise intelligence.

AI does not replace humans. It repositions us to a place no system can follow: understanding, deciding, designing, and creating.

At Keyrus, you will not just develop skills — you will develop judgment. Your expertise sharpens with every system you architect, every client challenge you solve, and every deployment that compounds on the last.

Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges data, AI, and human decision-making at scale, across industries and geographies. This is not a role you fill. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.

Role Details

📍 Job location: Spain (Hybrid model)
✈️ Travel: Available for monthly travel to Madrid or Lisbon
🕒 Contract type: Employee
🗓 Target start date: January 2027
⏰ Working hours: Full-time
💵 Compensation: €55k to €75k gross per year
🗣 Languages: Spanish and English

📋 What You'll Architect

As an AI Governance Lead, you will help organisations transform complexity into measurable outcomes by combining technology, data, intelligence, and human decision-making.

This role is both strategic and consultative — perfect for someone who can combine governance design, practical implementation, and leadership of client engagements. We’re looking for professionals who think like architects and act like builders.

You will translate regulatory requirements, organisational risk appetite, Responsible AI principles and business context into practical governance: roles, decision rights, risk classification, lifecycle gates, controls, evidence, human oversight and assurance. You define what must be governed, who is accountable, what evidence is required and when a decision must be escalated. Technical and operational teams remain responsible for implementing and operating the controls within their domains.

Responsibilities

• Design and operationalise AI Governance and Responsible AI operating models, defining roles, decision rights, forums, escalation paths, accountability and lifecycle responsibilities.

• Establish practical AI intake, inventory and risk-classification processes, so AI and agentic use cases receive proportionate governance based on their context and risk.

• Translate regulation, risk requirements and Responsible AI principles into actionable controls and evidence requirements, working with Legal, Compliance, Privacy and Security where interpretation falls outside the role.

• Define governance gates across the AI lifecycle, covering assessment, testing, human oversight, approvals, material changes, exceptions, deployment readiness and periodic review.

• Design Human in Command mechanisms, clarifying which decisions may be automated, which need human validation, who remains accountable and how escalation works.

• Assess whether governance controls operate effectively, reviewing documentation, testing evidence, approvals, monitoring, traceability and remediation.

• Govern AI consumption, including usage and budget policies, token costs and shadow AI.

• Guide architecture, engineering, data and delivery teams in turning required controls into practical implementation, while respecting their technical decision rights.

Create reusable governance assets, including playbooks, assessment methods, decision matrices, control libraries and documentation standards for future Keyrus engagements.

👤 Who You Are

• You are a governance professional who knows that trustworthy AI cannot be created through policy alone.

• You translate abstract principles and regulatory requirements into processes, decisions, controls and evidence that people can actually use.

• You are comfortable at the intersection of business, technology, risk, regulation and operations.

• You understand modern AI well enough to ask the right questions about models, RAG, agents, automated decisions and external providers, without presenting yourself as the engineer or architect.

• You challenge a solution when governance is insufficient, and you apply proportionality: not every use case needs the same level of control.

• You bring judgement, structure and pragmatism where regulation and technology are evolving at the same time.

🛠️ What You Bring

Qualifications & Experience

• Degree in Law, Risk Management, Information Systems, Computer Science, Business or a related field, or equivalent professional experience.

• Practical experience designing and implementing AI Governance, Responsible AI, model-risk, technology-risk or comparable governance frameworks in real organisations.

• Evidence of moving governance from policy into operation, for example through risk classification, intake processes, governance gates, approval workflows, control implementation, human oversight, assurance or remediation.

• Experience working across business, Legal, Risk, Compliance, Privacy, Security, Data, Architecture, Engineering and Operations stakeholders.

• Availability for monthly travel to Madrid or Lisbon.

• Professional fluency in Spanish and English, written and spoken.

Technical & Professional Skills

• Strong understanding of AI lifecycle risk and accountability, from use-case selection through design, deployment, operation and material change.

• Practical knowledge of the EU AI Act, GDPR and the AI, privacy, technology-risk and sector requirements applicable in Spain and the EU, including Spain's national AI legislation and AESIA supervision, with the judgement to involve Legal or regulatory specialists when required.

• Ability to translate regulatory, ethical, risk and policy expectations into operating requirements, decision rights, controls and evidence.

• A consulting posture, including the ability to run a governance maturity diagnostic tied to the client’s data and AI roadmap.

• Practical understanding of GenAI, RAG, agents, automated decision systems and production AI environments, sufficient to govern them effectively.

• Experience designing human oversight and decision-authority mechanisms (human-in-the-loop, human-on-the-loop, escalation, intervention).

• Experience conducting AI governance or Responsible AI assessments, readiness reviews, control reviews and assurance activities.

• Working knowledge of frameworks such as NIST AI RMF, ISO/IEC 42001 and ISO/IEC 23894, and the ability to adapt them pragmatically.

• Experience defining documentation and evidence requirements, including intended-use statements, risk assessments, evaluation evidence, limitations, approvals and audit trails.

• Experience governing third-party AI providers and external models, covering transparency, data use, dependency, security and operational risk.

• Data governance for AI: provenance, quality, usage rights and RAG sources.

Nice to Have

• Agentic AI governance, including autonomous actions, tool permissions, multi-agent systems, decision boundaries and stopping rules.

• Independent AI assurance, model validation, adversarial testing or red teaming.

• Experience with AI Governance, GRC, model-risk, privacy or evidence-management platforms.

• Enterprise Data Governance experience, where relevant to the assignment.

• Experience in highly regulated or safety-critical environments.

• Governance frameworks or operating models across multiple countries or jurisdictions.

• Consulting experience, and mentoring governance specialists or building reusable governance methodologies.

⭐ What Makes You Successful

• You focus on governance that operates, not governance that exists only in documentation.

• You distinguish between policy, control design, technical implementation, assurance and operational ownership.

• You apply governance in proportion to the actual risk and context of the system.

• You make accountability and decision rights explicit.

• You understand enough about modern AI to identify meaningful risks without trying to replace technical specialists.

• You know when an issue needs Legal, Security, Privacy, Architecture, Engineering or another specialist.

• You challenge weak evidence and unclear accountability constructively.

• You create practical governance patterns that can be reused and sustained after the engagement ends.

🎁 What We Offer at Keyrus Spain

• Competitive salary, paid in 14 instalments (option for 12 from day one).

• Annual performance bonus.

• Meal allowance (Restaurant Tickets): €1,800/year net, distributed over 11 monthly reloads

• Flexible retribution plan: transport & daycare tickets

• Private medical insurance with Sanitas (no copays, dental included)

• 22 days of annual leave, increasing every 3 years (up to 26 days)

• 14 public holidays (Madrid calendar)

• December 24th and 31st are considered company holidays when they fall on working days

• Continuous learning via KLX – Keyrus Learning Experience

• A collaborative, international, and human-centred work environment

💰 How Our Salary Ranges Work

At Keyrus, salary ranges reflect different levels of mastery and impact within the same role — not different job titles.

• Bottom of the range
  You meet the core requirements and will need ramp-up time and support.

• Middle of the range
  You are fully autonomous from Day 1 and deliver consistently.

• Top of the range
  You are a reference for the role, mentor others, and raise the bar for the team.

Final offers are based on experience, autonomy, scope, and market context, and are discussed transparently during the process.

🔒 Responsible AI & Recruitment

At Keyrus, all stages of our recruitment process are conducted and evaluated by human recruiters and interviewers.
To support accuracy and efficiency, AI may occasionally be used internally by our team exclusively for note-taking purposes during interviews. AI is never used to make decisions.

To ensure fairness, authenticity, and the protection of confidential and proprietary information, the use of AI tools by candidates during the recruitment process is strictly prohibited.

Our commitment to responsible AI practices ensures that hiring decisions are based solely on each candidate’s own skills, experience, judgment, and expertise.

⚠️ Any use of AI assistance during the interview process may result in immediate disqualification from the recruitment process.

♿ Equal Opportunity Statement

We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic.