AI Engineer

UMATR; Dubai; On-site; AED 260,000 - 450,000; Full time

Job summary

UMATR is building the next generation of AI-powered solutions in Dubai, with a small engineering team that values initiative and practical impact. You will contribute to production AI systems, backend services, and AI agents, shaping how the business applies AI across functions.

You will design, deploy and continuously improve AI workflows, leverage LLMs, RAG and semantic search, and collaborate closely with engineers to deliver reliable, scalable applications.

Qualifications

• 4+ years of experience developing AI applications or working in AI/software engineering roles involving production AI systems.
• Strong hands-on experience with Python and backend development.
• Hands-on experience building AI-powered applications using LLMs, with exposure to technologies such as RAG, AI agents or tool calling.
• Understanding of REST APIs and integrating AI capabilities into existing applications.
• Familiarity with vector databases, semantic search or retrieval-based systems.
• Comfortable working with other engineers, reviewing code and contributing to production applications.
• A proactive approach to problem-solving and an interest in learning new AI technologies.

Responsibilities

• Build and maintain production AI systems using Python, developing backend services and intelligent applications.
• Develop AI agents and automated workflows, including LLM integrations, tool calling, routing and orchestration.
• Design and improve RAG and GraphRAG systems, working with knowledge graphs, vector databases and semantic search.
• Build AI evaluation frameworks to measure retrieval quality, agent performance and reliability.
• Benchmark open-source LLMs and contribute to the transition towards self-hosted model infrastructure.
• Improve system reliability through monitoring, observability, automated testing and production support.
• Collaborate with engineering and business teams to translate operational challenges into practical AI solutions.
• Take ownership of development from initial design through to deployment and ongoing improvement.

Skills

Python

Backend development

LLMs

RAG

Tool calling

REST APIs

Vector databases

Semantic search

Docker

Kubernetes

Tools

Qdrant

Milvus

Job description

We're partnering with a forward-thinking organisation that's going beyond simply adopting AI, they're building it into the way their entire business operates.

With AI systems already running in production, they're investing in the next generation of intelligent technology, from autonomous AI agents and advanced retrieval systems to self-hosted LLMs.

And this is where things get exciting. You'll be joining a small engineering team with big ambitions, where your ideas won't get lost in layers of approval. You'll have the opportunity to influence technical decisions, experiment with emerging technologies and build AI solutions that make a real difference across the business.

Responsibilities

• Build and maintain production AI systems using Python, developing backend services and intelligent applications.
• Develop AI agents and automated workflows, including LLM integrations, tool calling, routing and orchestration.
• Design and improve RAG and GraphRAG systems, working with knowledge graphs, vector databases and semantic search.
• Build AI evaluation frameworks to measure retrieval quality, agent performance and reliability.
• Benchmark open-source LLMs and contribute to the transition towards self-hosted model infrastructure.
• Improve system reliability through monitoring, observability, automated testing and production support.
• Collaborate with engineering and business teams to translate operational challenges into practical AI solutions.
• Take ownership of development from initial design through to deployment and ongoing improvement.

Qualifications

• 4+ years of experience developing AI applications or working in AI/software engineering roles involving production AI systems.
• Strong hands-on experience with Python and backend development.
• Hands-on experience building AI-powered applications using LLMs, with exposure to technologies such as RAG, AI agents or tool calling.
• Understanding of REST APIs and integrating AI capabilities into existing applications.
• Familiarity with vector databases, semantic search or retrieval-based systems.
• Comfortable working with other engineers, reviewing code and contributing to production applications.
• A proactive approach to problem-solving and an interest in learning new AI technologies.

Preferred Skills

Experience in any of the following would be beneficial, but you don't need to have worked with all of them:

• GraphRAG, knowledge graphs or ontologies.
• LLM evaluation, retrieval metrics and regression testing.
• Qdrant, Milvus or other vector databases.
• Docker, Kubernetes or model-serving infrastructure.