Senior Manager - Artificial Intelligence

We are currently seeking a Senior Manager who will be responsible for designing, developing, and implementing cutting-edge AI solutions to solve complex business problems. Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to drive innovation and deliver AI-driven products and services. Our client, based in Dubai, is one of the leading multinational organisation in the region. This position is a contract role with an initial duration of 12 months and is renewable.Key Responsibilities:Establish and enforce AI assurance guardrails for model development and deployment across all AI initiatives. Review and approve AI solutions for production readiness, focusing on robustness, scalability, security, and operational fit. Ensure AI models adhere to enterprise standards for documentation, traceability, versioning, and lifecycle management. Partner with engineering and data science teams to embed assurance-by-design into AI delivery pipelines. Ensure AI solutions comply with Responsible AI, data governance, and regulatory requirements prior to deployment. Own and operationalize the AI Assurance Framework under the oversight of the AI Governance Board (AIGB). Act as the primary interface and subject‑matter authority to the AIGB on AI risk, ethics, compliance, and assurance matters. Prepare, present, and recommend AI use cases, risk assessments, and assurance outcomes for AIGB review and decision‑making. Ensure all AI initiatives comply with AIGB‑approved policies, Responsible AI principles, and enterprise risk appetite. Define escalation criteria and lead assurance reviews for high‑risk, sensitive, or mission‑critical AI use cases requiring AIGB approval. Coordinate with Legal, Risk, Cybersecurity, Compliance, and Audit to ensure integrated and defensible AI assurance decisions endorsed by the AIGB. Track, report, and follow up on AIGB actions, conditions, and assurance commitments across the AI lifecycle. Define enterprise standards for AI model validation, testing, and performance monitoring. Oversee independent evaluation of AI models for accuracy, bias, robustness, drift, and explainability. Ensure continuous monitoring of AI systems post‑deployment and define intervention thresholds. Lead assurance reviews for mission‑critical and safety‑impacting AI systems. Report AI assurance findings, risks, and mitigation plans to senior stakeholders. Act as a thought leader for AI Assurance across Technology & Infrastructure and the wider business. Mentor and coach team members and stakeholders on AI assurance, governance, and responsible AI practices. Develop and deliver AI assurance guidelines, playbooks, and training for technical and non‑technical audiences. Promote a culture where AI risk awareness and trust are embedded into delivery, not treated as an afterthought. Represent the organisation in external forums, audits, and industry discussions related to AI governance and assurance. Partner with the Head of Data & AI to shape the enterprise AI governance and assurance roadmap. Collaborate with business leaders to balance innovation speed with assurance requirements. Advise on AI strategy decisions related to agentic AI, automation, and advanced AI adoption. Support enterprise initiatives by ensuring AI assurance is aligned with current operations and future scale. Act as the single point of accountability for AI assurance engagement with vendors, partners, and regulators. Knowledge, skills & experience:Bachelor's degree or higher in Computer Science, Engineering, or a related field. 7-10 years' of overall experience and 5-7 years' of relevant experience.Solid experience in developing and implementing AI models and algorithms using frameworks such as TensorFlow, PyTorch, or Keras. Strong programming skills in languages such as Python, Java, or C++, with the ability to write clean, efficient, and maintainable code. Deep understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep neural networks, and reinforcement learning. Proficiency in data manipulation, analysis, and visualization using libraries such as NumPy, Pandas, and Matplotlib. Knowledge of cloud platforms and services, such as AWS, Azure, or Google Cloud, for building and deploying AI solutions. Experience with Azure AI cloud platforms and services, such as AI Foundry, Citadel, Azure ML, and other AI apps for building and deploying AI solutions. Familiarity with big data technologies, such as Hadoop and Spark, for processing and analyzing large-scale datasets. Knowledge of software engineering best practices, including version control, unit testing, and agile methodologies. Excellent problem-solving and analytical skills, with the ability to break down complex problems and propose innovative solutions. Strong communication skills to effectively collaborate with cross-functional teams and present complex AI concepts to non-technical stakeholders.