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.
- 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.