Job description:

Job TitleAI Governance Technical Lead E4.2Key Responsibilities Technical Leadership and StrategyLead the design and implementation of AI/ML architectures and solutions, including generative AI models, across diverse applications.Provide expert technical direction to AI/ML engineering teams to ensure scalable, high-quality, and robust solutions.Stay updated on AI/ML advancements, evaluating emerging technologies, frameworks, and tools for enterprise adoption. Team Management and MentoringManage and mentor AI/ML engineers and data scientists, fostering a collaborative and innovative environment.Conduct code reviews and provide feedback to uphold coding standards, performance, and best practices. Cross-Functional CollaborationWork closely with product managers, data scientists, and business stakeholders to define requirements and translate business needs into technical AI/ML solutions.Effectively communicate complex technical concepts and project outcomes to both technical and non-technical audiences. AI/ML Development and DeploymentOversee the full AI/ML software development lifecycle from design and development to deployment and maintenance.Ensure production-grade AI models are scalable, efficient, and reliable.Implement MLOps practices including model versioning, experiment tracking, and automated retraining pipelines. Responsible AI and GovernanceDevelop and enforce responsible AI practices aligned with ethical principles and regulatory standards.Ensure model governance, version control, and auditability across the AI lifecycle.Essential Qualifications and Skills Proven experience in leading AI/ML solution design and implementation. Strong background in AI/ML development, including generative AI and cognitive architectures. Experience managing technical teams and mentoring engineers. Deep understanding of MLOps, model deployment, and lifecycle management. Familiarity with responsible AI principles, governance frameworks, and compliance standards. Excellent communication and stakeholder engagement skills.Technical Skills and Knowledge AI/ML Development: Generative AI, supervised/unsupervised learning, reinforcement learning MLOps: Model versioning, CI/CD for ML, experiment tracking, retraining pipelines Responsible AI: Fairness, transparency, accountability, human oversight Governance Frameworks: ISO/IEC 42001, NIST AI RMF, EU AI Act compliance Cloud & Tooling: Azure AI, AWS SageMaker, Google Vertex AI, model monitoring and audit tools Security & Compliance: Model auditability, bias detection, secure deployment practicesEducation & Certification Advanced degree in AI/ML, Data Science, Computer Science, or related discipline Preferred certifications: o Responsible AI & Governance (ISO/IEC 42001, NIST AI RMF)o Cloud-native AI operationso MLOps and AI security certificationsLocation & Travel Flexible work model: Office or remote Occasional global travel

• Prepare detailed documentation including templates and frameworks for a cybersecurity solution to be proposed
• Carry out scoped studies including Risk analysis, Gap analysis for clients to technical solutions and document the findings and solution
• Ability to write innovatively and present frameworks that are developed for solutions
• Ability to define the opportunity and identify teams based on skills required and derive costing
• Define specific performance measures, targets, and goals to enable clients to measure success; articulate how the metrics contribute to the business case and link to client's overall strategy or mission