• Senior, hands-on engineer who ships, with recent production AI delivery experience.

  • Production LLM and agentic AI: RAG, orchestration and multi-step agent workflows.

  • MLOps depth: CI/CD, model registries, monitoring and evaluation pipelines.

  • Strong Python and modern software-engineering practice.

  • Consulting-adjacent skills to work with non-technical operational stakeholders, identify the real problem and manage

  delivery end to end.

  • Self-driven with minimal direction: scope the work, set the plan and drive it to production without waiting for a brief.

  • Technical leadership without formal authority across engineers, analysts and operational staff; ability to set adopted

  standards and influence senior stakeholders.

  • Strong product mindset: user feedback, feature prioritization, technical trade-offs and adoption.

  • Deep AI evaluation expertise: groundedness, hallucination detection, task success, latency, safety, business KPIs, A/B testing and continuous regression testing.

• Production AI cost optimization: model selection/routing, prompt and token optimization, caching and inference-cost management.

Desired Candidate Profile

• Bachelor's in Computer Science, Machine Learning, or a related quantitative field.

• 5+ years of hands-on experience in deploying and managing AI/ML models in production environments.

• Domain exposure to container terminals, maritime logistics, free zones or freight operations, including TOS data, gate and yard processes, customs/trade documentation, or warehouse/contract-logistics workflows.

• GCC or comparable multi-country regional experience; Arabic is a plus.

• Platform engineering or developer-experience background, including internal tooling adopted by other engineers.