Principal AI Product Engineer

About the Role

We are collaborating with a major organization based in Abu Dhabi that is pioneering and deploying cutting-edge AI solutions on a large scale. The position of Principal AI Product Engineer involves setting the technical standards for designing, constructing, and delivering AI-driven products throughout the organization.

This senior individual contributor role demands advanced AI engineering knowledge combined with strong product insight. Responsibilities span across the full lifecycle—from AI backend development and APIs to user interface creation. You'll also define best practices concerning Retrieval-Augmented Generation (RAG), Agentic AI systems, evaluation methodologies, and AI-native software development techniques.

Key Responsibilities

• Lead the complete architecture and deployment of AI production products, including backend systems, APIs, and user-centric applications.
• Architect scalable RAG frameworks and Agentic AI workflows involving tool integrations, planning mechanisms, and human-in-the-loop processes.
• Define engineering standards for AI-native development, encouraging reusable components, coding agents, development frameworks, and evaluation tools.
• Develop and mentor teams on backend service development utilizing Python and modern API technologies.
• Create dependable AI applications capable of managing data streaming, failure handling, latency challenges, and other production-grade requirements.
• Implement robust evaluation strategies focusing on grounding accuracy, retrieval effectiveness, regression detection, and performance monitoring.
• Establish and promote reusable technical standards, reference architectures, and components applicable to various AI products across the organization.
• Provide hands-on technical leadership including architecture assessments, engineering best practices, and mentorship while actively contributing to product delivery.

Required Qualifications and Skills

• Demonstrated experience at a senior individual contributor level (Staff or Principal) with a history of delivering production-ready systems actively used by customers.
• Expert Python programming abilities with extensive experience deploying LLM (Large Language Model)-driven applications in live environments.
• In-depth expertise with RAG, retrieval pipelines, Agentic AI concepts, agent orchestration, and AI backend service development.
• Strong understanding of LLM behavior patterns and common challenges including hallucinations, context degradation, latency issues, and model evaluation techniques.
• Proven track record managing end-to-end AI products covering backend, API layers, and frontend interfaces.
• Hands-on knowledge of leading Agentic AI and LLM platforms such as LangChain, LangGraph, or equivalents.
• Proficiency with contemporary tech stacks including React for frontend, APIs, PostgreSQL databases, containerization with Docker, cloud platforms, and CI/CD pipelines.
• Experience with AI evaluation frameworks encompassing retrieval quality measurement, grounding validation, regression testing, and both offline and online performance assessment.
• Practical experience integrating AI coding agents and AI-centric development practices within daily software engineering routines.
• Competence in crafting reusable engineering standards, tools, and architectures that enhance AI product development across engineering teams.
• Experience delivering AI solutions in complex or regulated sectors is considered an advantage.