مهندس ذكاء اصطناعي وتعلم آلي أول (Senior AI & ML engineer)

Job Summary

The Senior AI & ML engineer will design, build, and deploy AI systems to address complex enterprise challenges, delivering measurable business outcomes. This full-time, on-site role in Amman, Jordan involves working on in-house products and client projects locally and internationally.

Responsibilities

• Lead AI/ML engineering efforts from feasibility and design through deployment and ongoing enhancement for products and client engagements.
• Create LLM applications, RAG pipelines, and agentic AI systems that utilize enterprise data with defined execution limits and human oversight.
• Conduct data analysis, feature engineering, and model training or adaptation, collaborating on data pipelines and quality.
• Develop evaluation methods and test frameworks to measure model quality, retrieval effectiveness, agent behavior, and system reliability.
• Work on production readiness aspects including monitoring, scalability, failure management, security, and governance, ensuring observability and intervention mechanisms.
• Evaluate tradeoffs involving quality, latency, cost, and business value, and provide evidence of outcomes post-deployment.
• Research and prototype new AI approaches, improve in-house capabilities through iterative releases, and guide production adoption and integration.
• Support and mentor engineers, contribute to technical standards and reusable patterns, and assist client teams with documentation and capability transfer.

Requirements

• Minimum 3 years of hands-on AI/ML experience, including at least 2 years with Generative AI and LLMs.
• Proven experience owning design, build, deployment, and support of AI/ML solutions in production, including performance evaluation and failure handling.
• Strong Python programming skills and solid foundations in computer science, algorithms, software engineering, statistics, and machine learning.
• Practical experience with LLM applications and RAG, including embeddings, retrieval, context construction, and evaluation.
• Experience building agentic systems with tool integration, execution boundaries, and human intervention; multi-agent system experience is a plus.
• Familiarity with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
• Experience integrating AI systems with APIs, data pipelines, and cloud platforms like AWS, Azure, or GCP.
• Engineering mindset focused on evaluation, reliability, scalability, cost, and operational ownership post-deployment.
• Ability to communicate effectively with non-technical stakeholders, translating business problems into technical requirements and explaining results and tradeoffs.
• Proactive, able to work through uncertainty and share knowledge within a growing team.
• Bachelor’s or master’s degree preferred in Computer Science, Data Science, AI, or related field, or equivalent practical experience.

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