Senior AI Engineer

Client of Reqiva; Dubai; On-site; AED 420,000 - 720,000; Full time

Job summary

Client of Reqiva is seeking a Senior AI Engineer in Dubai to own AI-enabled features across backend services and LLM integrations. You will drive production deployments, observability, and cost efficiency in cloud and Kubernetes environments.

The role focuses on building scalable AI-powered software, RAG workflows, and high-performance distributed systems with modern AI tooling and agent-based automation, taking features from development through production.

Qualifications

• Experience building AI-enabled software in production.
• Strong background in backend services and APIs.
• Experience with LLM integrations and distributed systems.

Responsibilities

• Build and maintain AI-powered features.
• Develop production LLM integrations.
• Work on RAG and agent tool-use workflows.
• Context management, model routing and evaluation.
• Build reliable asynchronous and distributed systems.
• Improve performance, reliability and operating cost.
• Deploy and operate AI workloads in cloud and Kubernetes environments.
• Use AI coding agents to improve engineering productivity.
• Take ownership of features from development through production.

Skills

Python

Golang

Production AI

LLM applications

RAG

Kafka

Kubernetes

AWS

gRPC

Observability

Distributed systems

Cloud infrastructure

Tools

vLLM

Ray

Job description

We re working with a technology business in Dubai that is building sophisticated AI-powered products and is looking for a strong Senior AI Engineer to join its growing engineering team.

This is a hands-on engineering role for someone who has gone beyond experimenting with AI and has experience building, deploying and maintaining AI-enabled software in production. You ll work across backend engineering, LLM integration and distributed systems, taking ownership of features from initial development through deployment, observability and ongoing improvement.

What you ll be doing

Build and maintain AI-powered features

• backend services and APIs
• Develop production LLM integrations
• RAG and agent tool-use workflows
• Work on context management, model routing and practical AI evaluation
• Build reliable asynchronous and distributed systems
• Improve performance, reliability, responsiveness and operating cost
• Deploy and operate AI workloads within cloud and Kubernetes environments
• Use modern AI coding agents and automation to improve engineering productivity
• Take ownership of features from development through production

You ll ideally have strong experience with:

• Python and/or Golang
• Production AI and LLM applications
• RAG, tool use and agentic workflows
• Backend APIs and distributed systems
• Kafka, RabbitMQ, gRPC or similar technologies
• Kubernetes and cloud infrastructure, ideally AWS
• AI/LLM deployment and inference technologies such as vLLM or Ray
• Observability, testing and production reliability
• Experience with real-time AI, conversational AI, voice technologies or high-performance distributed applications would be particularly interesting

This would suit a strong engineer who enjoys figuring things out, learning new technologies and taking genuine ownership rather than simply working through predefined tickets.