Job at a Glance
- 📍 Location: Dubai, Dubai, United Arab Emirates
- 🏢 Company: Scale AI
- 💼 Employment Type: Full-time
- 📊 Seniority: Not Applicable
- 🗂️ Function: Engineering and Information Technology
- 🏭 Industry: Software Development
- 📅 Date Posted: 2026-08-07
- 🌐 Category: Artificial Intelligence
About the Role & Company
A new Engineering Manager, UAE opening at Scale AI in Dubai, Dubai, United Arab Emirates just went live. This is a Artificial Intelligence seat inside a team that’s shaping how the function scales locally. 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 Engineering Manager, UAE responsibilities plus the flex that comes with a growing team. The UAE market for artificial intelligence talent hasn’t cooled — compensation is competitive and net pay stays high thanks to the tax setup. 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
- Working knowledge of 6+ years of total software engineering experience, with a strong background in AI/ML engineering and full stack development
- 3+ years of engineering leadership experience, with a proven ability to handle and grow high
- Proven track record with on experience building, fine
- Comfort with proven experience in a customer
- Experience designing and integrating APIs at scale, including RESTful services and AI/ML APIs
- Ability to turn complex government what’s needed into practical, scalable engineering solutions under real delivery pressure
- Demonstrated strong communication and presentation skills, with the ability to tailor technical content for senior government audiences
- Familiarity with UAE government digital transformation priorities
Job Description
Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing governments around the world. Our core work consists of:
Creating custom AI applications that will impact millions of citizens
Generating high-quality training data for national LLMs
Upskilling and advisory services to spread the impact of AI
As these applications move from prototype to production, we’re investing heavily in the infrastructure and people that keep them reliable, secure, and trusted by our government partners.
At Scale, we’re not just building AI solutions – we’re enabling the public sector to transform their operations and better serve citizens through modern technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this Engineering Manager, UAE opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Machine Learning, LLM, Data Pipelines, Python, TensorFlow, PyTorch, Deep Learning, NLP, 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 (Engineering Manager, UAE) 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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