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Senior AI Engineer (LLM Systems)

Talent Seed • Switzerland
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Shape technical direction and build scalable AI products, focusing on LLM-based systems. Design and implement cutting-edge AI solutions, integrating infrastructure and human-centered design. Requires relocation to Riyadh/Dubai and strong software engineering fundamentals.

Key Highlights
Shape technical direction and bring AI concepts to life.
Turn prototypes into scalable, reliable products.
Design systems combining AI, infrastructure, and human-centered design.
Build production-grade LLM-based systems.
Design agentic systems and LLM evaluation frameworks.
Own systems end-to-end in production.
Technical Skills Required
AI Engineering LLM Prompt Engineering Software Engineering Python Cloud Infrastructure CI/CD Observability
Benefits & Perks
Relocation to Riyadh/Dubai

Job Description


**This role requires relocation to Riyadh/Dubai**


You’ll shape the technical direction and bring ambitious AI concepts to life, turning prototypes into scalable, reliable products that power next-generation customer experiences. Working closely with engineers, tech leads, and the CTO, you’ll design systems that combine cutting-edge AI, strong infrastructure, and human-centred design.


Experienced Required:


AI Engineering

  • Hands-on experience building complex, production-grade LLM-based systems across real-world use cases.
  • Advanced prompt engineering skills, with a strong intuition for how models interpret, prioritise, and follow instructions in multi-step and long-context workflows.
  • Deep understanding of LLM evaluation—recognising the limits of off-the-shelf metrics and able to design custom evaluation frameworks that measure what truly matters.
  • Experience designing agentic systems, including task decomposition, tool creation and orchestration, and reliability engineering for non-deterministic workflows.
  • Actively engaged with the evolving AI ecosystem—tracking research, experimenting with new capabilities, and translating emerging ideas into practical solutions.
  • Comfortable going beyond established patterns to design novel approaches when existing techniques are insufficient.


Software Engineering

  • Strong grasp of software engineering fundamentals, including clean abstractions, separation of concerns, and writing maintainable, extensible code.
  • Solid architectural judgment, with the ability to design systems that scale in complexity without sacrificing clarity or reliability.
  • Fluency in Python, including its idioms, trade-offs, and edge cases.
  • Comfortable owning systems end-to-end in production, including cloud infrastructure, observability, CI/CD, and operational lifecycle management.


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