Drive enterprise-scale AI strategy and architecture while leading multidisciplinary teams in a global IT consulting firm.
Responsibilities
Define and drive AI roadmaps aligned with corporate strategy
Oversee the full model lifecycle from research and experimentation to production deployment
Ensure measurable ROI and business impact from AI initiatives
Design LLM ecosystems including RAG pipelines, orchestration layers, and fine-tuning strategies
Lead domain-specific model fine-tuning and pretraining using proprietary datasets
Integrate platforms such as Azure OpenAI, AWS Bedrock, Anthropic Claude, and Google Vertex AI
Define governance, compliance, and security frameworks for LLM deployments
Establish evaluation standards for hallucination rate, factual accuracy, bias, and toxicity
Own data governance policies and feature store strategy
Lead model observability, monitoring, and drift management frameworks
Partner with DevOps and Security to ensure scalability, resilience, and compliance
Build and lead multidisciplinary AI teams including Data Scientists, ML Engineers, and Data Engineers
Mentor senior scientists and define research best practices
Communicate directly with executive leadership and non-technical stakeholders
Evaluate AI vendors and technology partnerships
Requirements
Master’s or PhD in AI, Machine Learning, Computer Engineering, or Applied Math or a related field
Minimum 7 years of overall professional experience
At least 2+ years in AI/ML leadership roles
Proven ability to build and scale enterprise-level AI/LLM platforms.
Visionary mindset driving innovation across business units.
Excellent executive communication and influence skills.
Focused on measurable ROI, scalability, and ethical AI.
Mentors senior scientists, defining best practices and research direction.
Benefits
Basic salary
Family Medical Insurance
Round-trip family flight tickets once per year
Visa coverage
Location: Dubai
Work Model: Hybrid – 2 days in the office and 3 days remote. If assigned to a project, you may be required to work from the client’s premises on a daily basis, depending on the project requirements.
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