Applied AI Engineer

We are looking for an Applied AI Engineer to design, build, and deploy production-grade AI systems at government scale.

The ideal candidate will have strong hands-on experience with LLMs, RAG, AI agents, evaluation frameworks, and production AI infrastructure, along with solid Python and software engineering fundamentals.

This role is focused on applying AI in real-world production environments rather than research prototypes alone.

Key Responsibilities

• Design and deploy production AI applications powered by large language models.
• Build end-to-end RAG systems, including document ingestion, embeddings, vector databases, semantic retrieval, reranking, and grounding evaluation.
• Develop AI agent systems supporting multi-step reasoning, planning, and tool use.
• Design and implement AI evaluation frameworks, including offline and online metrics, quality measurement and regression detection.
• Identify and address LLM limitations such as hallucination, context degradation, prompt sensitivity, latency, and output reliability.
• Develop reliable and scalable APIs for AI services.
• Integrate AI capabilities with existing platforms, applications, and data sources.
• Translate operational requirements into clearly defined engineering problems and measurable outcomes.
• Build reusable AI infrastructure and engineering patterns that can scale across multiple government entities.
• Ensure systems meet requirements for scalability, reliability, performance, and observability.

Required Qualifications

• 5+ years of experience in Applied AI Engineering, AI/ML engineering, or a combination of research and engineering.
• Demonstrated experience building and deploying production AI/ML systems.
• Strong proficiency in Python.
• Strong software engineering fundamentals, including system design, testing, debugging, and performance optimization.
• Deep understanding of Large Language Models (LLMs) and their behaviour and limitations.
• Experience designing or implementing AI evaluation frameworks.
• Understanding of offline evaluation, online monitoring, and regression detection.
• Strong knowledge of architecture, scalability, reliability, and observability.
• Strong written and verbal communication skills.

Preferred Qualifications

• MSc, PhD, or research experience in Computer Science, AI, ML, NLP, or a related field.
• Hands-on experience building RAG systems end-to-end.
• Experience with LangGraph, LangChain, AutoGen, Semantic Kernel, CrewAI, or similar frameworks.
• Knowledge of LLM inference behaviour, decoding strategies, prompt sensitivity, and latency optimization.
• Experience with vLLM, TGI, TensorRT-LLM, or equivalent GPU-based inference technologies.
• Experience with voice and conversational AI, including STT/TTS or real-time conversational systems.
• Publications, preprints, or research contributions in NLP, ML systems, retrieval, or related areas.

Pay: From AED8,000.00 per month

Work Location: In person