Senior AI Engineer
Takamol Holding
Date: 2 weeks ago
City: Riyadh
Contract type: Full time
Job Description
Drive the development and implementation of AI use cases across our organization. Lead the technical execution of high-impact projects, transforming business requirements into scalable AI features for both internal and external products. Operate with a high degree of autonomy, owning the full development lifecycle. Lead projects technically, set high architectural standards, and mentor others.
Key Responsiblities
Job Requirements
Drive the development and implementation of AI use cases across our organization. Lead the technical execution of high-impact projects, transforming business requirements into scalable AI features for both internal and external products. Operate with a high degree of autonomy, owning the full development lifecycle. Lead projects technically, set high architectural standards, and mentor others.
Key Responsiblities
- Own the execution of AI initiatives from ideation and data preparation to deployment and scaling.
- Design and optimize Generative AI solutions, including RAG architectures and LLM integrations, to solve real-world automation and intelligence challenges.
- Design and optimize Generative AI solutions, including RAG architectures and LLM integrations, to solve real-world automation and intelligence challenges.
- Design and manage efficient data flows and pipelines to ensure AI models are backed by robust, production-ready data.
- Take ownership of the technical roadmap for specific use cases, ensuring best practices in code quality, system reliability, and performance.
Job Requirements
- Bachelor’s degree in computer science, artificial intelligence, IT or a similar field.
- +3 years of professional experience in AI Engineering, Machine Learning, or a closely related software engineering field.
- Proven expertise in Generative AI (LLMs, RAG, and prompt engineering).
- Strong foundation in Traditional ML (classification, regression, and predictive analytics).
- Expert proficiency in Python and experience with modern data science libraries.
- Experience working within cloud ecosystems and data warehouses to manage large-scale datasets and orchestrate data flows.
- A track record of moving projects from prototype to production, ensuring they are scalable and reliable for end-users.
- Strong understanding of containerization (e.g., Docker) and AI deployment lifecycles is a significant advantage.
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