Lead AI Engineer

Overview

Lead AI Engineer

Dubai

AI and Machine Learning Engineering

• Architect and develop agentic AI systems capable of autonomous decision-making, tool usage, memory, and workflow orchestration.
• Build production-grade ML and LLM-powered applications, including recommendation systems, copilots, summarisation tools, and automation engines.
• Design and maintain high-performance ML pipelines, including model training, evaluation, and monitoring.
• Lead implementation of RAG, vector search, and other generative AI patterns.

Fintech and Domain Contributions

• Apply AI techniques to problems across the financial services spectrum, such as risk assessment, customer intelligence, fraud detection, and operational optimisation.
• Use domain knowledge in CFDs and A-book vs. B-book models to design intelligent decision heuristics and improve business outcomes.
• Partner with finance, risk, sales, and product teams to translate business needs into AI solutions.
• Engineering and Architecture:
• Lead development of full-stack AI applications, covering both back-end microservices and front-end interfaces.
• Build scalable systems using Python and modern web technologies (e. g., React, Node.js, FastAPI, and Django).
• Ensure best practices in reliability, scalability, security, and cloud-native deployment.
• Oversee integration of AI systems into existing infrastructure and business workflows.
• Leadership and Collaboration:
• Provide technical leadership and mentorship to AI/ML engineers.
• Drive the AI roadmap, architectural direction, and technology choices.
• Work cross-functionally with engineering, product, finance, and operations to identify opportunities for AI innovation.

Requirements

• Expert-level proficiency in Python for AI and ML engineering.
• Hands-on experience with LLMs, agentic frameworks, vector databases, and prompt engineering.
• Strong background in machine learning, deep learning, and applied statistics.
• Solid full-stack engineering skills (front-end + back-end).
• Strong understanding of APIs, microservices, cloud platforms, and MLOps (Azure AI factory)

Domain Knowledge

• Background in finance, trading, or financial technology.
• Understanding of CFDs and A-book/B-book operating models.
• Familiarity with financial risk, liquidity, and market dynamics is advantageous.

Other Competencies

• Ability to translate business needs into scalable AI architectures.
• Strong problem-solving, analytical, and communication skills.
• Proven experience delivering AI products end-to-end in production.

Preferred Qualifications

• Master's or PhD in Computer Science, AI, Engineering, or a related technical field.
• Experience in fintech, quantitative finance, or financial risk systems.
• Experience with high-performance or real-time systems.

Perks

• Each of our offices has its special perks; be it ‘no ties’, free lunches, charity events, or a hybrid work policy – but whenever you walk into an Equiti office, you’re sure to see a friendly face.
• We encourage international collaborations and always keep our eyes open to how we can do more.
• The benefits you can expect at your Equiti workplace include:
• Competitive salary package
• Performance-based bonus
• Medical insurance coverage for employees and family members
• Smart working options.
• Employee wellness initiatives.
• Personalized career development.
• Company lunch in the office.
• Regular company events.
• With energy, drive, and imagination, there’s no limit to where your career can go at Equiti.
• With a diverse workforce and geographical spread of offices, we strongly support career development initiatives as well as provide a range of opportunities for professional and life experiences.
• Equiti is an equal opportunity employer.
• “Equiti” refers to a group of companies consisting of seven regulated financial services companies licensed to operate in the respective jurisdictions of their incorporation, in addition to our tech and marketing hubs.
• Equiti has presence in Africa, Europe, and the Middle East.