Senior AI Forward Deployed Engineer

Technical Competencies

Must-Have Technical Skills

• Production LLM and agentic AI experience, including RAG, orchestration, and multi-step agent workflows.
• MLOps depth covering CI/CD, model registries, monitoring, and evaluation pipelines.
• Strong Python and modern software engineering practice.
• AI evaluation covering groundedness, hallucination detection, task success, latency, safety, business KPIs, A/B testing, and regression testing.
• Production AI cost optimization through model selection and routing, prompt and token optimization, caching, and inference cost management.

Nice-to-Have Experience

• Domain exposure to container terminals, maritime logistics, free zones, freight operations, or related terminal, customs, warehouse, or 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.

Principal Responsibilities

• Embed with terminal operations, gate and yard planning, trade documentation, logistics, and economic-zone teams to deliver AI solutions against live business problems.
• Lead cross-functional delivery squads drawn from business and IT without formal authority over team members.
• Take LLM and agentic systems from prototype to embedded production, owning security, data governance, and operational handover.
• Build reusable components, prompt and agent templates, reference architectures, and internal libraries.
• Establish the Lab’s MLOps/AIOps foundation, including CI/CD, evaluation pipelines, monitoring, versioning, and deployment standards.
• Convert one-off builds into a documented, repeatable AI delivery methodology.
• Set and enforce coding norms, responsible-AI guardrails, and documentation standards across Lab delivery.