C

Gen AI Engineer (Arabic-Speaking, Riyadh-Based)

salary Salary :

SAR17,000 - 18,000 monthly

icon briefcase Job Type : Full Time

Number of Applicants

 : 

000+

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Job Description - Gen AI Engineer (Arabic-Speaking, Riyadh-Based)

Job type: Contract, Iqama and Medical


Job location: Riyadh
 

Required skills

 

 5+ years of professional experience in building Machine Learning models &
systems
 1+ years of hands-on experience in how LLMs work & Generative AI (LLM)
techniques particularly prompt engineering, RAG, and agents.
 Experience in driving the engineering team toward a technical roadmap.
 Expert proficiency in programming skills in Python, Langchain/Langgraph and
SQL is a must.
 Understanding of Cloud services, including Azure, GCP, or AWS
 Excellent communication skills to effectively collaborate with business SMEs
Roles & Responsibilities
 Develop and optimize LLM-based solutions: Lead the design, training, fine-
tuning, and deployment of large language models, leveraging techniques like
prompt engineering, retrieval-augmented generation (RAG), and agent-based
architectures.
 Codebase ownership: Maintain high-quality, efficient code in Python (using
frameworks like LangChain/LangGraph) and SQL, focusing on reusable
components, scalability, and performance best practices.
 Cloud integration: Aide in deployment of GenAI applications on cloud platforms
(Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD
processes.
 Cross-functional collaboration: Work closely with product owners, data scientists,
and business SMEs to define project requirements, translate technical details,
and deliver impactful AI products.
 Mentoring and guidance: Provide technical leadership and knowledge-sharing to
the engineering team, fostering best practices in machine learning and large
language model development.

Continuous innovation: Stay abreast of the latest advancements in LLM research
and generative AI, proposing and experimenting with emerging techniques to
drive ongoing improvements in model performance.

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