AI Engineers - AI Hub - Amman

Turning business priorities into practical, scalable AI and data solutions.

EXPERIENCE -5-8 years

PRIMARY FOCUS -AI, GenAI, analytics

WORKING STYLE -Hands-on and client-facing

Role purpose

The Data & AI Expert will identify, design and implement high-value AI, generative AI, intelligent automation and analytics solutions. The role combines strong technical delivery with business engagement, translating business requirements into usable solutions and measurable outcomes.

Key responsibilities

• Engage business stakeholders to understand problems, define use cases and translate requirements into solution designs and delivery plans.
• Design and implement AI, GenAI and intelligent automation use cases, including prompt-based experiences and workflow integration.
• Develop, test and improve prompts, grounding approaches and evaluation criteria for reliable AI outputs.
• Use SQL, data modelling and analytical techniques to prepare, explore and interpret data.
• Build or contribute to analytics products using Power BI, Microsoft Fabric or Databricks.
• Support solution testing, deployment, user adoption, documentation and knowledge transfer.
• Communicate technical concepts, trade-offs, risks and outcomes clearly to business and technical audiences.

Required experience and capabilities

• 5-8 years of relevant experience across data, analytics, AI or intelligent automation.
• Practical experience implementing AI or GenAI solutions and prompt engineering techniques.
• Strong SQL skills with experience in data modelling, analysis and data preparation.
• Hands-on exposure to Power BI, Microsoft Fabric or Databricks.
• Demonstrated ability to convert business requirements into technical and functional solutions.
• Understanding of responsible AI, data privacy, security and model-output validation principles.

Preferred qualifications

• Experience with Azure AI services, APIs, Python or low-code automation platforms.
• Experience delivering solutions in consulting, transformation or other stakeholder-intensive environments.

Professional attributes

What success looks like

• Prioritized AI and analytics use cases are converted into working solutions.
• Solutions are practical, well documented and aligned with user needs.
• Stakeholders understand solution value, limitations and implementation decisions.