Full Stack AI Engineer
At a glance
Mid-level AI Engineering role at Flatgigs. Dubai · full-time.
Pay not stated AI Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build full-stack features from early prototypes through production, covering web, backend and mobile applications
- Create AI workflows that use LLMs, prompt orchestration and automation to support business processes
- Develop real-time and collaborative experiences using APIs, WebSockets and event-driven systems
- Design application architecture, connect services and databases, and deploy and monitor cloud-based products
What you bring
- Hands-on experience building AI products with LLMs, automation, prompt orchestration and API integrations
- Strong frontend and backend skills with React, TypeScript, Next.js, Node.js, Express and Python
- Cloud deployment experience with AWS, Azure or GCP, plus relational and NoSQL database knowledge
- Four to six years of full-stack engineering experience across web and mobile development
Who this fits
This role suits a mid-level engineer comfortable owning features across the stack, from initial design through deployment and iteration. The job is onsite in Dubai.
From the employer
Our client is a newly formed technology venture backed by one of the UAE’s most established family-owned conglomerates and a fast-growing technology company.
The business was created with a clear mission: to digitalise, automate, and connect operations across a diversified group of companies with a strong legacy in the UAE market. The wider group has decades of operating history and a portfolio spanning travel and tourism, logistics and delivery, real estate, car rental, and food and beverage.
Our focus is to build practical, scalable technology products that solve real operational challenges across these businesses - from connecting systems and automating workflows to launching new digital platforms that improve efficiency, customer experience, and commercial performance.
These products will first be built and proven within a live business ecosystem, then taken to market as commercial solutions for wider industries. This gives the team a unique opportunity to work on technology that has immediate real-world use, strong business backing, and long-term market potential.
ABOUT THE ROLE
We are looking for two highly capable Full-Stack AI Developers with proven experience building AI-native products and intelligent automation systems from the ground up.
The ideal candidates should be comfortable working across the full stack and owning end-to-end delivery of new user-facing features, from rapid 0-to-1 prototyping to production-ready implementation. This includes building agentic AI workflows, real-time collaborative experiences, and scalable AI-powered applications.
Candidates must have hands-on experience working with LLMs, workflow automation, prompt orchestration, API design/integration, and modern AI development frameworks. Strong engineering fundamentals across frontend, backend, and cloud infrastructure are essential.
You should be confident working with relational and NoSQL databases, designing scalable architectures, and deploying applications across cloud environments such as AWS, Azure, or GCP.
Experience across web, backend, and mobile application development is required.
Requirements
TECHNOLOY EXPERTISE REQUIRED
- React, TypeScript, and Next.js for building scalable, responsive, and high-quality web applications
- Node.js, Express for backend services, API development, and real-time application logic
- Python for backend development, automation, AI integrations, and workflow orchestration
- Cloud infrastructure across AWS, Azure, or GCP, including deployment, scalability, monitoring, and production operations
- Experience integrating these technologies into AI-native products, real-time systems, and end-to-end digital platforms
PREFERRED EXPERIENCE
- 04 to 06 Years of Experience in Full Stack Engineering including Web & Mobile Development
- Building and delivering web and mobile applications across the full product lifecycle
- Integrating LLMs into real-world applications, including prompt design, AI tooling, and orchestration
- Designing agentic AI workflows, automation pipelines, and AI-enabled business processes
- Developing real-time systems, collaborative features, and event-driven applications
- Building and consuming REST APIs, WebSockets, and microservices-based architectures
- Working with LLMs, vector databases, RAG pipelines, embeddings, and AI search/retrieval systems
- Implementing CI/CD pipelines, scalable deployments, cloud-native infrastructure, and production-grade engineering practices
- Taking ownership of features end to end - from architecture and development to deployment, monitoring, and iteration