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.
