We are looking for AI Lead Engineer to join one of our clients team in Abu Dhabi, United Arab Emirates.
Purpose of the role:
To lead the AI architecture function for digital transformation projects, serving as the strategic authority for both cloud-native and on-premise AI ecosystems. The role requires advanced technical mastery in Agentic-AI, Generative AI, Machine Learning, MLOps, AgentOps, LLMOps, LLM Finetuning, alongside the consultancy skills to assess AI opportunities, design high-performance AI stacks, and estimate cost-to-value ratios. The Lead will ensure that AI solutions are seamlessly integrated into the enterprise fabric, including Dynamics 365 and existing data ecosystems.
Location: Abu Dhabi
Key Responsibilities:
- AI Strategy & Consultancy: Act as a senior consultant to identify and assess AI use cases, evaluating them for business value, technical feasibility, and architectural fit within the digital transformation roadmap.
- Architecture Design: Architect and oversee the deployment of end-to-end AI stacks using Azure AI Foundry and on-premise enterprise solutions. This includes designing for Inference Engines, Vector Databases, and Agent Builders.
- Sizing & Cost Estimation: Perform detailed technical sizing of AI infrastructure (Compute/GPU/Token usage) and provide accurate cost-benefit analysis for both Azure cloud and on-premise implementations.
- Agentic & Gen-AI Leadership: Lead the design and implementation of Agentic-AI workflows and Multi-Agent Systems, ensuring robust orchestration and goal-alignment. LLM Finetuning for Arabic language is also needed.
- Operations (MLOps/LLMOps/AgentOps): Establish and enforce standards for the AI lifecycle, focusing on automated deployment, monitoring of agentic behavior, and model performance optimization.
- Integration: Design architectures that bridge on-premise data security with Azure AI capabilities, ensuring seamless data flow between the AI stack and the Medallion data architecture.
- Compliance & Governance: Ensure all AI architectures comply with federal AI ethics guidelines, focusing on data privacy and responsible AI.
- Technical Troubleshooting: Resolve complex issues related to model latency, vector embedding quality, and integration bottlenecks within the AI pipeline.
- Leadership & Mentoring: Guide AI engineers and data scientists, fostering a culture of excellence in all data activities.
Requirements
- Certifications: Microsoft Azure AI Engineer Associate and Azure Solutions Architect Expert certification.
- Experience: Minimum of 8 years in AI/Machine Learning, with at least 3 years in a Lead Architect capacity for large-scale enterprise projects.
- Hands-on Mastery: Deep experience with Azure AI Foundry, Vector Databases (e.g., Weaviate, Azure AI Search, vLLM), and Inference Engines (e.g., Nvidia Triton, vLLM, etc)
- Advanced AI Paradigms: Proven track record in delivering Agentic-AI and Generative AI solutions at an enterprise level.
- Technical Stack: Proficiency in AI and ML frameworks, Python, Agentic Workflow, and containerization (Kubernetes/Docker).
- Consultancy Skills: Strong ability to translate complex AI concepts into architectural blueprints and financial estimates for stakeholders
- 6 + years relevant exp. ideally working with consulting firms, big 4 or government entities
- Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
- Language: Proficiency in Arabic and English is required
Competencies
- AI Technical Leadership: Ability to set the vision for the AI stack.
- Financial Acumen: Proficiency in AI cost modeling (Tokenomics & Infrastructure).
- Analytical Thinking: Breaking down business problems into AI-solvable components.
- Collaboration: Working closely with the Data Architect Lead to leverage enterprise data for AI.
- Adaptability: Staying ahead of the rapidly evolving AI landscape
