Senior AI Solutions Engineer - UAE

Responsibilities

Design and deploy production-grade AI applications powered by large language models, including assistants, copilots, and automation tools.

Build advanced agent-based systems capable of multi-step reasoning, planning, and tool integration.

Develop end-to-end retrieval-augmented generation (RAG) systems, including data ingestion pipelines, vector databases, and retrieval optimisation.

Expose AI capabilities through scalable APIs that integrate seamlessly with existing systems and data platforms.

Define and implement evaluation frameworks to measure model performance, detect issues, and continuously improve system quality.

Translate complex and ambiguous requirements into structured engineering solutions with clear success metrics.

Build reusable components, frameworks, and infrastructure to enable scalable AI adoption across multiple entities.

Collaborate with cross-functional teams to deliver reliable, high-performance AI systems.

Requirements

7+ years of experience in applied AI, machine learning engineering, or software engineering roles.

Strong programming skills in Python, with solid software engineering fundamentals including system design, testing, and performance optimisation.

Proven experience building and deploying AI/ML systems in production environments.

Hands-on experience working with large language models and deploying LLM- powered applications.

Strong understanding of the challenges of deploying AI systems in production, including latency, reliability, and model behaviour.

Experience designing scalable, reliable, and high-performance systems.

Desired Experience

Experience building RAG systems end-to-end, including retrieval pipelines and vector search.

Familiarity with agent-based frameworks such as LangChain, LangGraph, AutoGen, or similar.

Experience designing evaluation frameworks for AI systems, including performance monitoring and regression detection.

Exposure to conversational AI systems, including speech or real-time interaction pipelines.

Experience working with modern AI inference infrastructure and deployment environments. 7+ years of experience in applied AI, machine learning engineering, or software engineering roles.

Strong programming skills in Python, with solid software engineering fundamentals including system design, testing, and performance optimisation.

Proven experience building and deploying AI/ML systems in production environments.

Hands-on experience working with large language models and deploying LLM- powered applications.

Strong understanding of the challenges of deploying AI systems in production, including latency, reliability, and model behaviour.

Experience designing scalable, reliable, and high-performance systems.

Experience building RAG systems end-to-end, including retrieval pipelines and vector search.

Familiarity with agent-based frameworks such as LangChain, LangGraph, AutoGen, or similar.

Experience designing evaluation frameworks for AI systems, including performance monitoring and regression detection.

Exposure to conversational AI systems, including speech or real-time interaction pipelines.

Experience working with modern AI inference infrastructure and deployment environments.