Job at a Glance
- 📍 Location: Dubai, United Arab Emirates
- 🏢 Company: Discovered MENA
- 💼 Employment Type: Full-time
- 📊 Seniority: Mid-Senior level
- 🗂️ Function: Information Technology
- 🏭 Industry: Technology, Information and Media
- 📅 Date Posted: 2026-09-09
- 🌐 Category: Artificial Intelligence
About the Role & Company
Discovered MENA has an open Senior Agentic AI Engineer role based in Dubai, United Arab Emirates. The Artificial Intelligence group at Discovered MENA has been on an upward hiring curve — a good signal for anyone joining now. Whether you’re mid-career or a step above, this kind of role tends to pay back in exposure and lateral growth. You’ll cover the core Senior Agentic AI Engineer remit, with room to pick up adjacent work as the team matures. The UAE market for artificial intelligence talent hasn’t cooled — compensation is competitive and net pay stays high thanks to the tax setup. Bottom line — the mix of growth stage, market position and role scope makes this worth a serious look for the right applicant.
Key Requirements
- 5+ years of experience in AI/ML Engineering, ideally within a product
- on experience building and deploying production
- Hands-on time with proven experience deploying
- Working knowledge of experience with LLMs such as LLaMA, Mistral, GPT or Claude, alongside agent frameworks such as LangChain, Semantic Kernel, CrewAI or MCP
- Practical experience with RAG, prompt engineering, LLM evaluation, fine
- Strong Python programming skills and experience building scalable AI workflows, backend services and production applications
- Practical grasp of experience with Docker, Kubernetes, CI/CD, MLOps and AI lifecycle management
- Solid grasp of secure system design, including authentication, authorisation, data isolation, encryption and audit logging
Job Description
We’re partnering with an practical technology organisation in Dubai that’s developing advanced AI products and intelligent automation solutions.
Senior Agentic AI Engineer to design, build and deploy production-grade AI agent systems, with a particular focus on secure, private and self-hosted environments.
This is a role for someone who goes beyond experimenting with LLMs. You’ll take ownership of end-to-end AI solutions, from architecture and model deployment through to agent orchestration, application development and production operations. You’ll also contribute to the development and optimisation of commercial AI products, working closely with product and engineering teams to turn complex business what’s needed into scalable solutions.
Design, build and deploy production-grade AI agent applications using self-hosted LLMs and modern agentic frameworks.
Build secure, private AI architectures with strong data isolation, access controls, encryption and auditability.
Build end-to-end agent workflows that integrate with enterprise systems, internal applications and business processes.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this Senior Agentic AI Engineer opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, LLM, MLOps, Model Deployment, SQL, TensorFlow, PyTorch, Machine Learning, Deep Learning, NLP. 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 (Senior Agentic AI Engineer) 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
#DubaiJobs #AIJobs #ArtificialIntelligence #Hiring #DubaiAI #JobAlert #Get9to5Jobs
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