Principal AI Product Engineer – Abu Dhabi
Discover the Opportunity:
We’re partnering with a leading organisation in Abu Dhabi that is building and deploying advanced AI products at significant scale.
They’re looking for a Principal AI Product Engineer to set the technical standard for how production AI products are designed, built and delivered across the organisation.
This is a senior individual contributor role for someone who combines deep AI engineering expertise with strong product judgement. You’ll work end-to-end across AI backends, APIs and user interfaces, while defining best practices around RAG, Agentic AI, evaluation and AI-native software development.
Discover the Responsibilities:
- Own the end-to-end architecture and delivery of production AI products, from AI backend and APIs through to user-facing applications.
- Design and establish scalable RAG architectures and Agentic AI workflows, including tool use, planning and human-in-the-loop patterns.
- Define AI-native engineering practices, including the use of coding agents, reusable components, development frameworks and evaluation tooling.
- Build and guide the development of production backend services using Python and modern API technologies.
- Develop reliable AI applications that effectively handle streaming, failures, latency and other real-world production requirements.
- Establish strong evaluation practices across grounding, retrieval quality, regression detection and production performance.
- Define reusable technical standards, reference architectures and components that can be adopted across multiple AI products.
- Provide technical leadership through architecture reviews, engineering standards and mentorship while remaining highly hands-on with delivery.
Discover the Requirements:
- Proven experience operating at Staff, Principal or equivalent senior IC level, with a strong track record of shipping production systems used by real users.
- Strong Python engineering skills with substantial hands-on experience building LLM-powered applications in production.
- Deep experience with RAG, retrieval pipelines, Agentic AI, agent orchestration and AI backend services.
- Strong understanding of LLM behaviour and failure modes, including hallucination, context degradation, latency and model evaluation.
- Experience owning AI products end-to-end across backend services, APIs and user-facing interfaces.
- Hands-on experience with modern Agentic AI and LLM frameworks such as LangChain, LangGraph or similar technologies.
- Comfortable working across a modern technology stack, including React, APIs, PostgreSQL, Docker, cloud environments and CI/CD.
- Experience with AI evaluation frameworks, including retrieval quality, grounding, regression testing and offline/online evaluation.
- Strong experience using AI coding agents and AI-native development approaches as part of day-to-day software engineering.
- Experience designing reusable engineering standards, tooling and architectures that improve how wider engineering teams build AI products.
- Experience delivering AI products within complex or regulated environments would be advantageous.