Job at a Glance
- 📍 Location: Dubai, Dubai, United Arab Emirates
- 🏢 Company: TEN-XER
- 💼 Employment Type: Full-time
- 📊 Seniority: Not Applicable
- 🗂️ Function: Other
- 🏭 Industry: Human Resources Services
- 📅 Date Posted: 2026-09-09
- 🌐 Category: Artificial Intelligence
About the Role & Company
TEN-XER is hiring a AI Engineer, Generative AI and Agentic AI in Dubai, Dubai, United Arab Emirates. This position joins a Artificial Intelligence function that continues to attract investment in the UAE market. Whether you’re mid-career or a step above, this kind of role tends to pay back in exposure and lateral growth. Expect the standard AI Engineer, Generative AI and Agentic AI responsibilities plus the flex that comes with a growing team. GCC demand for artificial intelligence skills is still healthy, and Dubai continues to sit at the top of the regional pay bands. It’s a solid entry point for candidates who want regional exposure without giving up ownership of real work — you’re contributing, not observing.
Key Requirements
- Over 10 years of experience in AI development, with specific hands-on experience in Generative and Agentic AI
- Deep understanding of machine learning principles, neural network architecture, and natural language processing
- solving skills and ability to innovate using latest AI technologies
- Master’s or Doctoral degree in Computer Science, Artificial Intelligence, Machine Learning, or related field
- Experience with AI model deployment in real
- Strong communication skills and ability to articulate complex technical concepts to non
- Proven leadership experience in managing large and diverse engineering teams
- Familiarity with data privacy and ethical considerations specific to AI solutions
Job Description
Responsibilities: – Design, build, and optimize modern AI models with a focus on Generative and Agentic AI applications. – Work closely closely with cross-functional teams to integrate AI solutions into existing products and services. – Conduct research to advance the state of the art in AI, contributing to publications in top-tier journals and conferences. – Put in place robust machine learning algorithms that enhance the performance and capabilities of AI systems. – Lead the development of scalable AI systems, ensuring high efficiency and accuracy. – Evaluate and improve existing AI models to align with the latest technological advancements. – Mentor junior engineers and drive initiatives for professional development within the AI team.
What’s needed: – Over 10 years of experience in AI development, with specific hands-on experience in Generative and Agentic AI. – Proven track record of developing large-scale AI systems in a commercial setting. – Strong programming skills in Python, TensorFlow, PyTorch, or similar AI frameworks. – Deep understanding of machine learning principles, neural network architecture, and natural language processing. – Strong problem-solving skills and ability to innovate using latest AI technologies.
Qualifications: – Master’s or Doctoral degree in Computer Science, Artificial Intelligence, Machine Learning, or related field. – Extensive publication history in reputable AI conferences and journals is desirable. – Experience with AI model deployment in real-world applications. – Strong communication skills and ability to articulate complex technical concepts to non-technical stakeholders. – Proven leadership experience in managing large and diverse engineering teams.
Additional Skills: – Experience with cloud-based AI solutions and architectures. – Familiarity with data privacy and ethical considerations specific to AI solutions. – Ability to work on-site full-time and lead collaborative projects effectively. – Familiar with agile development methodologies and version control systems.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this AI Engineer, Generative AI and Agentic AI opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, TensorFlow, PyTorch, Machine Learning, Model Deployment, Deep Learning, NLP, LLM, Computer Vision, MLOps. ATS parsers match exact strings, not synonyms.
- Use a single-column layout. Two-column resumes break parsers — text gets scrambled or dropped.
- Save as .docx or standard .pdf (not scanned/image PDF). Avoid text boxes, headers, footers, graphics.
- Use standard section headings: Experience, Education, Skills, Certifications.
- Mirror the exact job title (AI Engineer, Generative AI and Agentic AI) in your target role line where truthful.
- Quantify results with numbers, percentages, currency. Metrics improve ATS scoring and human review.
- Spell acronyms out once (e.g., Search Engine Optimization (SEO)) so parser catches both forms.
- Font: Arial, Calibri, or Times New Roman at 10-12pt. Fancy fonts can render as unreadable glyphs.
Top 10 Interview Questions for This Role
- Walk me through your background and why you’re interested in this role.
- Describe a challenging project you owned end-to-end. What was the outcome?
- Tell me about a time you disagreed with a stakeholder. How did you handle it?
- How do you prioritize when everything on your plate feels urgent?
- How do you decide between fine-tuning a model vs. prompt engineering?
- Explain overfitting to a non-technical stakeholder.
- Walk through your data validation pipeline for training data.
- How do you evaluate model performance beyond accuracy?
- Describe your MLOps setup — from experimentation to production.
- How do you handle model drift once a system is in production?
How to Apply
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