Principal AI Product Engineer

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.

• 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.

• 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 Lang Chain, Lang Graph 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.