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.