Lead AI Engineer

Job Title: Lead AI Engineer

Location: Abu Dhabi, UAE

About the Role:

We are looking for a Lead AI Engineer to lead the design, development, deployment, and continuous improvement of production-grade AI solutions. The role combines hands-on AI engineering, technical leadership, solution architecture, and team mentoring, with a strong focus on Generative AI, LLMs, Computer Vision, AI Agents, Machine Learning, and AI-powered enterprise products.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• 7+ years of experience in software engineering, AI/ML engineering, or related technical roles.
• 3+ years of hands-on experience building and deploying AI/ML or Generative AI solutions.
• Demonstrated experience leading AI/ML engineering teams or technically leading complex AI projects.
• Strong experience taking AI solutions from PoC → production → scale.
• Strong software engineering and system-design fundamentals.

Key Responsibilities:

• Lead the architecture, development, and deployment of AI/ML solutions across enterprise and smart-city use cases.
• Design and implement Generative AI, LLM, RAG, AI Agent, Computer Vision, NLP, and predictive analytics solutions.
• Evaluate and integrate commercial and open-source AI models based on performance, cost, latency, security, and data-residency requirements.
• Develop and optimize LLM applications, including prompt engineering, RAG pipelines, embeddings, vector databases, model fine-tuning, and agentic workflows.
• Lead the deployment of AI models on cloud, on-premises, and GPU infrastructure.
• Develop scalable AI services and APIs that can be integrated with existing enterprise platforms and products.
• Establish MLOps/LLMOps practices, including model versioning, evaluation, monitoring, CI/CD, observability, and lifecycle management.
• Optimize AI solutions for accuracy, inference performance, GPU utilization, latency, and operational cost.
• Work with software engineering teams to integrate AI capabilities into .NET, web, mobile, IoT, and enterprise platforms.
• Lead technical PoCs and rapidly convert successful prototypes into production-ready products.
• Establish AI engineering standards, reusable frameworks, development guidelines, and best practices.
• Conduct technical evaluations of emerging AI models, frameworks, and technologies.
• Mentor and provide technical direction to AI Engineers, ML Engineers, Data Scientists, and other technical resources.
• Ensure AI solutions comply with organizational security, privacy, responsible AI, and governance requirements.
• Collaborate with business and product teams to identify opportunities where AI can deliver measurable business value.
• Support technical proposals, RFPs, solution architecture, estimations, and client presentations when required.

Required Technical Skills:

Generative AI & LLM

• Strong experience with LLMs such as GPT, Claude, Gemini, Qwen, Llama, or equivalent.
• Hands-on experience with RAG, embeddings, vector databases, prompt engineering, function/tool calling, and AI agents.
• Experience with LLM evaluation, hallucination reduction, guardrails, and model optimization.
• Knowledge of fine-tuning techniques such as LoRA/QLoRA is highly desirable.

AI/ML & Computer Vision

• Strong understanding of machine learning and deep learning concepts.
• Experience with PyTorch and/or TensorFlow.
• Experience with Computer Vision frameworks such as YOLO, OpenCV, or equivalent.
• Experience with NLP, OCR, classification, detection, prediction, and anomaly-detection solutions.

AI Infrastructure & MLOps

• Experience deploying AI workloads using Docker and Kubernetes.
• Strong understanding of GPU-based AI infrastructure and inference optimization.
• Experience with cloud AI platforms, preferably Microsoft Azure.
• Experience with model serving technologies and AI inference frameworks is highly desirable.
• Understanding of MLOps/LLMOps, CI/CD, model monitoring, logging, and observability.

Software Engineering

• Strong Python development skills.
• Good understanding of REST APIs, microservices, databases, and distributed systems.
• Experience integrating AI services with enterprise applications.
• Knowledge of .NET/C# and Angular is an advantage.
• Experience with SQL and NoSQL databases is desirable.

Leadership Responsibilities

• Provide technical leadership for the AI engineering team.
• Review architecture, code, AI models, and technical designs.
• Define development standards and engineering practices.
• Break down complex AI initiatives into deliverable technical components.
• Estimate technical effort, infrastructure requirements, and implementation timelines.
• Identify technical risks and recommend mitigation strategies.
• Coach engineers and build internal AI engineering capabilities.
• Act as the technical authority for AI engineering decisions within assigned projects.

Required Certifications:

• Microsoft Azure AI Engineer Associate or equivalent.
• AWS/GCP AI or ML certification.
• Kubernetes or cloud architecture certification.
• MLOps/AI engineering certifications are an advantage.