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.