Job Description

Roles & Responsibilities

Discover the Opportunity We re partnering with a major government entity in Abu Dhabi that is building next-generation AI capabilities to power large-scale, real-world systems across the public sector. This role sits within a central AI function responsible for developing and deploying advanced AI applications across multiple entities. The team is focused on leveraging cutting-edge technologies including large language models, retrieval systems, and agent-based workflows to deliver scalable, production-grade solutions. This is a unique opportunity to work at the forefront of applied AI, contributing to the development of AI-driven systems that operate at national scale.

Discover the Role As an Applied AI Engineer, you will design and deliver end-to-end AI-powered applications, working at the intersection of AI engineering, software development, and product delivery. You will take ownership of building robust, production-ready systems leveraging modern AI capabilities, translating complex requirements into scalable solutions. This role requires strong hands-on engineering expertise combined with a deep understanding of how to operationalise AI in real-world environments.

Discover the 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.

Discover the 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.

Discover the Desired

• 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.

Desired Candidate Profile

• 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.