Lead AI Engineer

Equiti is a pioneering fintech firm and world-class provider of multi-asset fintech products - from liquidity solutions to in-house tech hubs to online trading platforms. With over 400 global specialists in 9 languages, Equiti provides clients with access to individual, professional, and institutional brokerage services in Europe, the Middle East, and Africa.

At Equiti, we believe that financial opportunities can unlock potential for everyone, everywhere. We’re on a mission to deliver accessible online trading products around the world through education and accessibility.

Think finance is stuffy? Think again.

At Equiti, we’re building fintech with a purpose: making wealth tools accessible to everyone. As we continue to grow, we’re seeking talented individuals who thrive in innovative environments. , and we are on the lookout for talented individuals who can perform and excel in a dynamic and innovative working environment. Our Technology department would like to welcome a detail-oriented.

Lead AI Engineer in our office in Dubai

We are looking for an experienced Lead AI Engineer to drive the design and development of advanced AI systems within our fintech ecosystem. This role blends expertise in agentic AI, large language models (LLMs), machine learning, and full-stack engineering with a strong understanding of financial products, including CFDs and A-book/B-book models. You will be responsible for architecting scalable AI solutions, building intelligent automation, and creating AI-driven products that enhance decision-making, user experience, and operational efficiency across the business.

The core responsibilities for the job include the following:

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.