Principal Artificial Intelligence Engineer

Role Summary

We seek an experienced Principal AI/ML Engineer based in Abu Dhabi to lead the end-to-end development and deployment of enterprise-level AI and machine learning systems. This role involves working closely with interdisciplinary teams and senior stakeholders to deliver scalable, secure, and measurable AI solutions aligned with strategic objectives.

Key Responsibilities

• Take full ownership of the AI/ML solution lifecycle, from initial research and experimentation to production deployment and ongoing optimization.
• Establish and enforce AI/ML architectural guidelines, engineering standards, ensuring security, maintainability, and cost-efficiency across projects.
• Design and implement advanced machine learning, deep learning, and generative AI models utilizing appropriate tools and frameworks.
• Champion MLOps best practices including continuous integration and delivery (CI/CD), model version control, monitoring, and lifecycle management.
• Collaborate with product owners, architects, and engineering teams to turn business requirements into actionable AI solutions that create tangible value.
• Mentor and lead engineering teams through capability development, design critiques, and knowledge exchange to foster best engineering practices.
• Conduct technical discovery, proof-of-concept initiatives, and architectural evaluations to guide AI strategy and identify business improvement opportunities with AI.
• Ensure that responsible AI principles, thorough documentation, and governance are incorporated throughout delivery for compliance and operational excellence.
• Keep abreast of and evaluate emerging AI technologies and trends to shape organizational adoption and innovation.

Experience and Skills

• Demonstrated extensive experience deploying AI/ML solutions in live, production-grade environments.
• Advanced proficiency in Python and familiarity with machine learning libraries such as PyTorch, TensorFlow, and Scikit-learn.
• Comprehensive understanding of machine learning methods, deep learning architectures, and generative AI technologies.
• Experience using cloud platforms including Azure, AWS, or Google Cloud Platform.
• Solid grasp of MLOps, CI/CD pipelines, automated testing, and software engineering best practices.
• Proven leadership experience in guiding technical teams and making architectural decisions.
• Prior work experience in consulting or solution integration environments is highly valued.