AI Ethics & Compliance Lead

O projekcie: At Virtusa( former ITMAGINATION), every innovator has the potential to transform and lead in a digital world—but unlocking that potential takes more than technology; it takes a trusted partner who combines engineering excellence, creativity, and an AI-first mindset. Together, we co-create solutions that help businesses grow faster, operate smarter, and make experiences better with technology. We are seeking a specialized AI Ethics & Compliance Lead (T3) to join our Poland delivery center. In this role, you will be the primary authority responsible for ensuring that our AI/ML solutions are developed and deployed responsibly, ethically, and in full alignment with global regulatory standards. With 6–8 years of experience in risk management, compliance, or governance, you will bridge the gap between high-level ethical principles and technical execution. You will work directly with engineering squads to bake "Compliance by Design" into our AI lifecycles, ensuring transparency, fairness, and auditability for our global enterprise clients. Wymagania: - 6–8 years of professional experience in Governance, Risk, and Compliance (GRC), with a significant focus on AI/ML or highly regulated digital transformation projects.   - Deep, hands-on expertise in implementing NIST AI RMF, OECD AI Principles, and ISO/IEC 23894. You should be able to demonstrate how you have applied these to real-world AI projects.   - Comprehensive knowledge of GDPR (specifically regarding automated decision-making and profiling), HIPAA (for PHI protection), and SOC 2 trust service criteria. (Familiarity with the EU AI Act is highly preferred for the Poland center).   - Strong conceptual understanding of Large Language Models (LLMs), NLP, and classical ML algorithms. You must understand how models are trained and deployed to identify points of ethical risk effectively.   - Practical knowledge of XAI techniques and tools to ensure that AI-driven outcomes can be audited and understood by non-technical stakeholders.   - Proven ability to use bias-detection tools and frameworks to evaluate model fairness and implement remediation strategies.   - Experience developing risk registers, defining control frameworks, and leading impact assessments (DPIA/AIA).   - Background in supporting or leading technical audits for enterprise-grade software or AI systems.   - Exceptional communication skills with the ability to influence C-suite executives, legal counsel, and technical engineering leads.   - Ability to translate legal and ethical "prose" into technical "requirements" for developers and data scientists.   - Master’s degree in Law, Computer Science, Philosophy (focused on Tech Ethics), or a related field.   - High level of integrity, analytical rigor, and the ability to navigate ambiguous regulatory landscapes.   - Native or C1-level English is mandatory for global client interaction and policy documentation.   - Experience working within Agile/Scrum environments using Jira for tracking compliance tasks. Codzienne zadania: - AI Governance & Framework Implementation: Define and execute an AI governance strategy aligned with OECD AI Principles, the NIST AI Risk Management Framework (RMF), and ISO/IEC 23894. Establish clear policies for every stage of the AI lifecycle: from design and development to deployment and continuous monitoring. - Regulatory Compliance & Data Protection: Serve as the subject matter expert for GDPR, HIPAA, and SOC 2 within the context of AI. Conduct comprehensive Data Protection Impact Assessments (DPIA) and AI-specific risk assessments to ensure privacy and security. - AI Risk Management: Develop and maintain a living AI Risk Register. Identify and mitigate risks related to algorithmic bias, performance degradation (drift), and explainability gaps. Define risk scoring models that guide go/no-go decisions for model deployment - Responsible AI Practices: Establish and lead an AI Ethics Review Board. Set the standards for Explainable AI (XAI), non-discrimination, and human-in-the-loop oversight to ensure accountability across all automated decisions. - Audit, Controls & Assurance: Design a robust AI controls framework. Support both internal and external audits (including SOC 2 and regulatory inquiries), ensuring full traceability of AI decisions and thorough documentation of model training and data lineage. - Monitoring & Continuous Compliance: Establish KPIs and Key Risk Indicators (KRIs) for AI governance. Implement continuous monitoring systems for bias detection and compliance adherence throughout the model production life. - Cross-functional Collaboration: Act as the strategic liaison between Data Science/Engineering, Legal, and Business stakeholders, translating complex regulatory requirements into actionable technical controls.