وظيفة مهندس ذكاء اصطناعي شاغرة في الرياض لدى جهة غير معلنة

AI Engineer

Location: Riyadh, Saudi Arabia

Employment Type: Full-Time

Department: Technology / AI & Data

Experience Level: Mid-Level Experience

Required: 4-6 years

About the Role

We are looking for an experienced AI Engineer to join our Technology / AI & Data team in Riyadh. The successful candidate will design, build, integrate, and deploy reliable AI solutions that address real business challenges and deliver measurable value.

The role requires hands-on experience in machine learning, generative AI, large language models, retrieval-augmented generation, and production-grade AI application development. You will work closely with software engineers, data engineers, data scientists, and business stakeholders to convert business requirements into scalable and secure AI products.

Arabic language proficiency is preferred, particularly for candidates who have experience developing Arabic-language AI applications, conversational systems, or solutions for Arabic data and business environments.

Key Responsibilities

•Design, develop, test, and deploy machine learning and artificial intelligence solutions for enterprise use cases.

•Build generative AI applications using large language models and modern AI platforms.

•Develop retrieval-augmented generation solutions using enterprise data, knowledge bases, embeddings, and vector search.

•Build AI-powered assistants, chatbots, recommendation systems, and intelligent agents.

•Integrate AI models and services with enterprise applications through REST APIs and other integration methods.

•Prepare, clean, transform, and analyze structured and unstructured data for AI applications.

•Develop prompt strategies, evaluation processes, retrieval pipelines, and model-usage patterns that improve accuracy and reliability.

Work with embeddings, vector databases, semantic search, and knowledge retrieval technologies.

•Evaluate AI solutions for quality, relevance, performance, security, scalability, and cost efficiency.

•Fine-tune or customize machine learning and language models when required.

•Build proofs of concept and convert successful prototypes into production-ready services.

•Develop reusable APIs, services, and components that enable AI capabilities across the organization.

•Monitor deployed AI applications and continuously improve their performance and reliability.

•Apply responsible AI practices related to data privacy, security, governance, explainability, and access control.

•Stay current with developments in generative AI, machine learning, AI engineering frameworks, and cloud technologies.

Required Qualifications and Experience

•Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computer Engineering, or a related field.

•4-6 years of professional hands-on experience in AI engineering, machine learning engineering, data science, software engineering with an AI focus, or a related technical discipline.

•Strong programming skills in Python.

•Practical experience with machine learning and deep learning concepts and frameworks.

•Demonstrated experience building and deploying generative AI or LLM-based applications.

•Hands-on experience designing and implementing RAG architectures.

•Practical knowledge of embeddings, vector databases, semantic search, and retrieval pipelines.

•Experience integrating AI and machine learning models through APIs and software applications.

•Good understanding of software engineering principles, data structures, algorithms, APIs, and system design.

•Experience with Git and modern software development practices.

•Strong analytical, troubleshooting, and problem-solving skills.

•Ability to communicate technical concepts clearly to both technical and non-technical stakeholders.

Preferred Technical Skills

Experience with several of the following technologies is highly desirable:

AI and Machine Learning

•PyTorch, TensorFlow, or scikit-learn

•Hugging Face Transformers

•Natural language processing and deep learning

•Model evaluation, monitoring, and optimization

•Fine-tuning, model customization, or inference optimization

Generative AI and LLM Engineering

•OpenAI, Azure OpenAI, Anthropic, or other LLM platforms

•LangChain, LangGraph, LlamaIndex, or similar frameworks

•Prompt engineering and structured output generation

•AI agents, function calling, and tool use

•LLM evaluation and guardrails

•Experience with Arabic NLP, Arabic language models, or multilingual AI applications

Data, Search, and Integration

•SQL and PostgreSQL

•Pinecone, Qdrant, Weaviate, Milvus, Chroma, or other vector databases

•Elasticsearch or OpenSearch

•REST APIs and FastAPI

•Data processing for documents, text, and other unstructured data

Cloud and Deployment

•Microsoft Azure, AWS, or Google Cloud

•Docker and containerized deployments

•CI/CD pipelines

•Kubernetes is a plus

•Experience with logging, monitoring, observability, and production support

Key Competencies

•Business-oriented mindset with a focus on measurable outcomes.

•Ability to translate business requirements into practical and scalable AI solutions.

•Strong ownership and ability to deliver projects from concept through production.

•Clear communication and effective collaboration across multidisciplinary teams.

•Ability to work independently while contributing to a collaborative engineering culture.

•Curiosity and willingness to learn rapidly in a fast-changing AI landscape.

•High standards for quality, security, privacy, and responsible use of AI.

Preferred Candidate Profile

The preferred candidate is an AI Engineer with 4-6 years of relevant professional experience who has delivered real-world machine learning or generative AI solutions in production. Experience with Arabic-language data, Arabic NLP, multilingual models, or enterprise solutions serving Arabic-speaking users will be considered a strong advantage.

Arabic proficiency is preferred but should be evaluated as a job-related capability rather than a nationality requirement. Candidates must be able to work effectively in English in a technical and professional environment.