Job at a Glance
- 📍 Location: Dubai, United Arab Emirates
- 🏢 Company: TechBiz Global
- 💼 Employment Type: Full-time
- 📊 Seniority: Mid-Senior level
- 🏭 Industry: Software Development
- 📅 Date Posted: 2026-09-09
- 🌐 Category: Artificial Intelligence
About the Role & Company
TechBiz Global is hiring a AI Engineer – Security in 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. You’ll cover the core AI Engineer – Security remit, with room to pick up adjacent work as the team matures. GCC demand for artificial intelligence skills is still healthy, and Dubai continues to sit at the top of the regional pay bands. Bottom line — the mix of growth stage, market position and role scope makes this worth a serious look for the right applicant.
Key Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Cybersecurity, or a related field
- Proven experience in developing and deploying machine learning or deep learning models, preferably in a security context
- Strong programming skills in Python (and/or R, Java, or C++), with experience in ML frameworks such as TensorFlow, PyTorch, or Scikit
- Solid understanding of cybersecurity principles, threat landscapes, and security operations
- Experience working with large datasets, data preprocessing, and feature engineering
- Familiarity with cloud platforms (AWS, Azure, or GCP) and their security services
- solving skills and ability to work in a fast
- Experience with security tools (e
Job Description
At TechBiz Global, we’re providing recruitment service to our TOP clients from our portfolio.
we’re currently looking for a highly proactive and careful
AI Engineer – Security to join one of our clients’ teams . If you’re looking for an exciting role to grow in an practical environment, this could be the perfect fit for you.
Key Responsibilities: – Design, build, and put in place AI/ML models for threat detection, anomaly detection, and incident response. – Analyze large-scale security datasets to identify patterns, trends, and emerging threats. – Work closely with cybersecurity teams to integrate AI solutions into existing security infrastructure (e.g., SIEM, SOAR platforms). – Continuously monitor and improve the performance of deployed AI models to reduce false positives/negatives. – Research and evaluate new AI techniques and tools relevant to cybersecurity challenges. – Build automation scripts and tools to streamline security operations using AI/ML. – Document model architectures, processes, and findings for technical and non-technical stakeholders. – Make sure compliance with data privacy, security policies, and industry regulations in all AI-driven initiatives. – Participate in incident investigations, providing AI-driven insights and recommendations. – Stay current with advancements in AI, cybersecurity threats, and best practices.
Must have: – Bachelor’s or Master’s degree in Computer Science, Data Science, Cybersecurity, or a related field. – Proven experience in developing and deploying machine learning or deep learning models, preferably in a security context. – Strong programming skills in Python (and/or R, Java, or C++), with experience in ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. – Solid understanding of cybersecurity principles, threat landscapes, and security operations. – Experience working with large datasets, data preprocessing, and feature engineering. – Familiarity with cloud platforms (AWS, Azure, or GCP) and their security services. – Strong problem-solving skills and ability to work in a high-tempo, collaborative environment. – Strong written and verbal communication skills.
Nice to have: – Industry certifications such as CISSP, CEH, or relevant AI/ML certifications. – Experience with security tools (e.g., SIEM, SOAR, IDS/IPS) and their integration with AI solutions. – Knowledge of adversarial machine learning and AI model robustness techniques. – Experience with DevSecOps practices and CI/CD pipelines for ML models. – Familiarity with regulatory frameworks (GDPR, HIPAA, etc.) and their impact on AI in security. – Contributions to open-source AI or security projects. – Experience with natural language processing (NLP) for security use cases (e.g., phishing detection, threat intelligence analysis)
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this AI Engineer – Security opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, TensorFlow, PyTorch, Machine Learning, Deep Learning, NLP, LLM, Computer Vision, MLOps, Data Pipelines. 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 – Security) 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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