AI Adoption and Transformation Lead
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Key skills for this role
About the Role
finera. is looking for an AI Adoption and Transformation Lead to own the AI strategy, adoption roadmap, and governance. This hands-on role involves identifying high-value use cases, enabling controlled adoption of generative AI and automation, and building the governance layer.
Key Skills for This Role
Responsibilities
- Develop the AI strategy in line with business priorities and risk appetite.
- Maintain a practical roadmap from short term pilots to long term maturity, underpinned by an AI maturity model.
- Define KPIs, ownership, timelines, and governance checkpoints; report progress to senior management.
- Work with department heads to surface opportunities; assess each on value, complexity, data sensitivity, regulatory impact, risk, and ROI.
- Lead pilots, PoCs, and controlled rollouts; translate requirements into functional specs.
- Coordinate internal teams, vendors, and business users ensuring every use case has a clear owner, defined process impact, measurable benefit, and human accountability model.
- Create an AI system inventory (tools, use cases, owners, data types, vendors, risk ratings) and approval workflows.
- Coordinate AI risk assessments across privacy, security, confidentiality, bias, explainability, resilience, and regulatory exposure.
- Partner with Legal, Security, and Data Protection to align with GDPR, EU AI Act, ISO 27001, PCI DSS, DORA, NIS2, and internal policies.
- Embed human in the loop controls for high impact use cases.
- Prevent confidential, regulated, or personal data from reaching public AI tools.
- Mitigate AI specific risks: prompt injection, data leakage, hallucination, insecure integrations, uncontrolled agents, and vendor lock in.
Requirements
- AI adoption, digital transformation, automation, or technology delivery in a business or regulated context
- Practical generative AI, LLM, agent, and workflow automation knowledge; translating business needs into technical solutions
- Running pilots through to production; working with senior stakeholders and cross functional teams
- Evaluating vendors, building business cases, and managing third party risk
- Governance, risk, security, or compliance; creating policies, frameworks, or operating models
- Degree in Computer Science, Information Systems, Data Science, Engineering, Business Technology, or related field — or equivalent experience
Full Job Posting
Job Description
- Own finera.’s AI strategy, adoption roadmap, and governance, and the practical delivery of AI enabled business solutions.
- This is a hands on transformation role working across business, technology, security, data protection, legal, compliance, operations, HR, and senior leadership.
- Key objectives include setting and maintaining the AI adoption roadmap, identifying and delivering high value use cases, enabling controlled adoption of generative AI and automation, building the governance layer, and keeping all initiatives aligned with security, privacy, compliance, and regulatory
Job Requirements
- AI adoption, digital transformation, automation, or technology delivery in a business or regulated context.
- Practical generative AI, LLM, agent, and workflow automation knowledge; translating business needs into technical solutions.
- Running pilots through to production; working with senior stakeholders and cross functional teams.
- Evaluating vendors, building business cases, and managing third party risk.
- Governance, risk, security, or compliance; creating policies, frameworks, or operating models.
Skills & Competencies
- Strong grasp of generative AI, LLMs, agents, automation, and data driven decision support.
- Understanding of prompt engineering, RAG, workflow design, and human review models.
- Ability to evaluate platforms and their limitations; working knowledge of APIs, integrations, access control, and cloud.
- Strong business analysis and process optimisation; sharp prioritisation and ROI focus.
- Roadmap, business case, and operating model development.
- Solid project management across planning, scheduling, dependency tracking, risk/issue management, and stakeholder reporting.
- Understanding of responsible AI, privacy, security, and operational risk; ability to assess data sensitivity and regulatory exposure.
- Familiarity with security and privacy by design; comfort working with legal, risk, and security stakeholders.
- Regulated environment experience highly desirable.
- Excellent written and verbal communication; able to explain complex AI in plain business language.
- Able to influence senior stakeholders, lead workshops, and drive governance discussions.
- Strong documentation discipline with a functional mindset ensuring concepts translate into execution.
Qualifications
- Degree in Computer Science, Information Systems, Data Science, Engineering, Business Technology, or a related field — or equivalent experience.
- Advantageous certifications: AI governance / responsible AI, cloud, project management, or business analysis.
- Practical and delivery oriented; analytical, curious, and innovation driven.
- Risk aware without being restrictive; balances speed, control, and value.
- Strong stakeholder management; able to challenge unrealistic AI expectations.
- Disciplined in documentation; high integrity and confidentiality.
Nice to Have / Preferred
- GDPR, EU AI Act, ISO 27001, PCI DSS knowledge in a financial services or fintech context.
- Third party and model risk management; internal audit experience.
- Enterprise AI platforms; vector databases and RAG; low code/no code automation.
- Secure software development practices.
Job Responsibilities
- Develop the AI strategy in line with business priorities and risk appetite.
- Maintain a practical roadmap from short term pilots to long term maturity, underpinned by an AI maturity model.
- Define KPIs, ownership, timelines, and governance checkpoints; report progress to senior management.
- Work with department heads to surface opportunities; assess each on value, complexity, data sensitivity, regulatory impact, risk, and ROI.
- Lead pilots, PoCs, and controlled rollouts; translate requirements into functional specs.
- Coordinate internal teams, vendors, and business users ensuring every use case has a clear owner, defined process impact, measurable benefit, and human accountability model.
- Create an AI system inventory (tools, use cases, owners, data types, vendors, risk ratings) and approval workflows.
- Coordinate AI risk assessments across privacy, security, confidentiality, bias, explainability, resilience, and regulatory exposure.
- Partner with Legal, Security, and Data Protection to align with GDPR, EU AI Act, ISO 27001, PCI DSS, DORA, NIS2, and internal policies.
- Embed human in the loop controls for high impact use cases.
- Prevent confidential, regulated, or personal data from reaching public AI tools.
- Mitigate AI specific risks: prompt injection, data leakage, hallucination, insecure integrations, uncontrolled agents, and vendor lock in.
Job Benefits
- Competitive salary package aligned with experience and market standards.
- Medical Insurance starting from day 1.
- Access to training resources and development opportunities that support your professional growth.
- Well stocked office with snacks, drinks, and refreshments available daily.
- A multinational organisation that promotes a strong, collaborative culture.
- Regular team building events and company activities that strengthen collaboration across teams.
- Employee Recognition Program celebrating our 'Employee of the Month' with special perks.
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