Key Skills

Job Description

Everience is an international consulting group delivering AI-augmented digital services and placing people at the heart of the AI revolution. With a presence in Europe, Africa, Asia and America, Everience offers its 4,000-strong workforce the most demanding and stimulating environment in which to transform and develop their skills, learning about new AI-based roles and building their future employability. Through its Symbiotic Academy the group offers a unique hub for training, practical application and exchange where everyone can experiment, learn, and progress in the fields of artificial intelligence and data. In accordance with its core purpose of orchestrating the symbiotic relationship between humans and AI in the workplace, Everience is making the augmented employee the driving force of a “symbiotic age”, where AI enhances talents and opens up new career opportunities. Job Description We are looking for an experienced Responsible AI Lead to help shape and operationalize responsible AI practices across a large, complex enterprise environment. In this role, you will act as a subject matter expert and trusted advisor on Responsible AI, helping ensure that AI solutions are designed, developed, and deployed responsibly, in line with business objectives, regulatory requirements, and established AI governance principles. You will work closely with AI, technology, risk, legal, governance, and business stakeholders to translate Responsible AI principles into practical standards, controls, assessments, and ways of working that enable safe and responsible AI adoption. Your Role As Responsible AI Lead, you will be responsible for embedding Responsible AI principles throughout the AI lifecycle. You will assess AI use cases, advise stakeholders on risks and mitigation measures, and help establish the governance framework needed to support responsible innovation at scale. Key Responsibilities Responsible AI Framework & Standards: Maintain and further develop Responsible AI principles, standards, guidance, and practices. Translate Responsible AI principles into practical requirements, controls, and assessment criteria for AI use cases. Work closely with Legal and other relevant stakeholders on requirements around fairness, transparency, explainability, accountability, and human oversight. Contribute to related AI quality, monitoring, documentation, discoverability, and AI lineage practices. AI Risk & Responsible AI Assessments Lead Responsible AI reviews for high-risk, business-critical, and complex AI solutions. Act as an AI Steward during the assessment and review of relevant AI use cases. Assess risks relating to bias, fairness, transparency, explainability, safety, accountability, and unintended consequences. Identify potential gaps and provide practical recommendations and mitigation actions. Support teams in addressing Responsible AI requirements before and throughout deployment. Governance & AI Lifecycle Integration Embed Responsible AI controls into AI lifecycle management processes and governance workflows. Partner with AI Governance and Operations teams to operationalize Responsible AI requirements through platforms, processes, and tooling. Support AI approval, risk assessment, and review processes. Work with relevant risk and governance committees to ensure Responsible AI considerations are incorporated into decision-making. Regulatory & Industry Alignment Monitor developments in AI regulation, standards, frameworks, and industry best practices. Advise business and technology teams on the implications of emerging AI regulations and requirements. Help translate regulatory expectations into practical enterprise controls and guidance. Support audit, assurance, and compliance activities relating to Responsible AI. Education, Awareness & Adoption Act as a senior Responsible AI subject matter expert and trusted advisor across the organization. Develop practical playbooks, guidance, training materials, and awareness initiatives. Support teams in understanding and applying Responsible AI principles throughout the AI lifecycle. Promote an approach where Responsible AI enables innovation and responsible adoption rather than unnecessarily restricting it. Qualifications 8–12+ years of experience in AI/ML, data science, AI governance, model risk, technology risk, or a related field. Strong experience assessing AI risks and advising on responsible AI practices. Practical experience with areas such as fairness, bias, transparency, explainability, accountability, and AI safety. Experience translating policies, principles, and regulatory requirements into practical controls and processes. Experience working with senior stakeholders and influencing enterprise-level decisions. Experience working in a large, regulated, or otherwise complex enterprise environment is highly desirable. Expertise Responsible AI and AI ethics. AI risk management and governance. Fairness, transparency, explainability, and AI safety. AI/ML lifecycle and model development practices. AI governance frameworks and control design. Understanding of relevant regulatory and industry frameworks, such as: EU AI Act NIST AI Risk Management Framework (AI RMF) ISO/IEC 42001 Ability to interpret policies and regulations and translate them into practical business and technology requirements. Personal Attributes Strong judgment, integrity, and a pragmatic approach to risk. Able to challenge stakeholders constructively while supporting innovation. Comfortable balancing business value, risk, regulatory requirements, and ethical considerations. Strong communication and stakeholder management skills. Able to influence through expertise, credibility, and collaboration. Passionate about building transparency, accountability, and trust around AI. Additional Information All our positions are open to both women and men and are, of course, open to people with disabilities.

Core Responsibilities

Develop and operationalize Responsible AI standards, controls, assessments, and governance across the AI lifecycle, including reviews of high-risk and complex AI use cases. Advise stakeholders on risk mitigation, regulatory alignment, governance processes, and practical training to support responsible AI adoption.

Requirements

Requires 8–12+ years of experience in AI/ML, data science, AI governance, model risk, technology risk, or a related field, with strong experience assessing AI risks and applying Responsible AI practices. Candidates should be able to translate policies and regulations into practical controls, understand relevant frameworks such as the EU AI Act, NIST AI RMF, and ISO/IEC 42001, and influence senior stakeholders in complex organizations.