Job at a Glance
- 📍 Location: Dubai, Dubai, United Arab Emirates
- 🏢 Company: QuantumFy Group
- 💼 Employment Type: Full-time
- 📊 Seniority: Mid-Senior level
- 🗂️ Function: Engineering and Information Technology
- 🏭 Industry: Financial Services
- 📅 Date Posted: 2026-08-10
- 🌐 Category: Artificial Intelligence
About the Role & Company
The Lead AI Engineer vacancy at QuantumFy Group sits in Dubai, Dubai, United Arab Emirates. The role sits inside a Artificial Intelligence team that’s actively expanding its footprint in the region. Whether you’re mid-career or a step above, this kind of role tends to pay back in exposure and lateral growth. Day-to-day you’d be working across the scope typical of a Lead AI Engineer — a mix of delivery and stakeholder work. Regionally, Dubai leads on both pay and visibility for artificial intelligence work; that hasn’t changed this year. 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
- 8+ years of production engineering with deep Python; distributed data platforms (Spark, Kafka or equivalents); graph databases and entity
- Experience in tax, financial crime, fraud, or other regulated
- Hands-on time with strong foundation in Computer Science, with hands-on experience in Software Development and designing scalable, secure, and maintainable systems
- Advanced skills in Neural Networks and Pattern Recognition, including experience building and deploying deep learning models in production
- on experience with Natural Language Processing (NLP), particularly in developing explainable, auditable models for regulated environments
- Experience with MLOps practices, including CI/CD for ML, containerization (Docker, Kubernetes), model monitoring, and lifecycle management
- Comfort with background in designing AI systems that comply with regulatory and security what’s needed; familiarity with standards relevant to financial services, energy, healthcare, or government is an advantage
- Demonstrated ability to lead cross
Job Description
Lead AI Engineer | Sovereign Tax Intelligence Platform
QuantumFy Group | Dubai/UAE (hybrid) | Full-time
QuantumFy Group builds agentic AI platforms for regulated and critical-infrastructure environments: banking, energy, healthcare, and large institutional operations gas/oil. Our platforms connect existing systems rather than replacing them, consolidate fragmented data into governed foundations, resolve entities into living graphs, detect patterns isolated systems can’t see, and convert approved recommendations into owned, auditable activity. Material decisions remain human-approved at all times. we’re scaling our engineering leadership for our most advanced platform work.
You own the technical delivery of the platform end to end. you’ll design and lead the build of the data foundation and integration layer across legacy government systems; the entity resolution and graph analytics capability; ML risk-scoring models with drift monitoring and outcome feedback loops; LLM and RAG components for case intelligence, with guardrails fit for a national authority; and the orchestration and audit layer that makes every recommendation traceable. You lead a senior squad, set the engineering standards, and represent the technical solution in front of a demanding institutional client alongside our leadership.
8+ years of production engineering with deep Python; distributed data platforms (Spark, Kafka or equivalents); graph databases and entity-resolution at scale; applied ML in production (risk scoring, anomaly detection) and modern LLM/RAG architecture; Kubernetes and hybrid cloud/on-premise deployment, including sovereign or air-gapped environments; a security and privacy mindset fluent in GDPR and the EU AI Act; and the seniority to lead engineers and stand in front of a government steering committee. Experience in tax, financial crime, fraud, or other regulated-data domains is a strong advantage. English fluent; Hungarian a plus.
Top-tier compensation, a leadership seat on a program of genuine national significance, a modular vendor-independent architecture you’ll shape from the first line, and a company of 100+ engineers across eight countries delivering for central banks, energy majors, sovereign programs, and healthcare systems.
ATS Resume Tips for This Role
To get past Applicant Tracking Systems (ATS) for this Lead AI Engineer opening, tailor your resume with the pointers below:
- Include these keywords verbatim in your Skills and Experience sections: Python, TensorFlow, PyTorch, Deep Learning, NLP, LLM, MLOps, Machine Learning, Computer Vision, 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 (Lead 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
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