AI Engineer

About the Role

We are seeking an experienced AI Engineer to join our Technology and AI & Data department based in Riyadh, Saudi Arabia. This full-time position involves designing, developing, integrating, and deploying dependable AI solutions tailored to address key business challenges while generating quantifiable value. The successful applicant will collaborate closely with software engineers, data engineers, data scientists, and business stakeholders to translate business needs into scalable, secure AI products.

Preference will be given to candidates with proficiency in Arabic, particularly those with background in developing Arabic-centric AI systems, conversational interfaces, or business solutions tailored to Arabic data.

Key Responsibilities

• Design, develop, test, and deploy machine learning and AI solutions for diverse enterprise scenarios.
• Create generative AI applications leveraging large language models and modern AI platforms.
• Implement retrieval-augmented generation (RAG) solutions utilizing enterprise data, knowledge bases, embeddings, and vector search technologies.
• Build AI-enhanced assistants, chatbots, recommendation engines, and intelligent agents.
• Integrate AI models and services with enterprise software via REST APIs and other methods.
• Prepare and transform structured and unstructured data for AI applications through cleaning and analysis.
• Develop prompt engineering strategies, evaluation workflows, and model usage patterns to optimize solution accuracy and dependability.
• Employ embeddings, vector databases, semantic search, and knowledge retrieval techniques.
• Assess AI solutions on quality, relevance, performance, security, scalability, and cost-efficiency criteria.
• Perform fine-tuning or customization of machine learning and language models as needed.
• Build prototypes and proofs of concept, advancing successful ones into production.
• Develop reusable APIs, services, and components to propagate AI capabilities throughout the organization.
• Monitor deployed AI applications to continually enhance their reliability and performance.
• Apply responsible AI principles addressing data privacy, security, governance, explainability, and access controls.
• Stay abreast of innovations in generative AI, machine learning frameworks, engineering methods, and cloud technologies.

Required Qualifications and Experience

• Bachelor’s degree in Computer Science, AI, Data Science, Software Engineering, or a related discipline.
• 4 to 6 years of practical experience in AI engineering, machine learning engineering, data science, or AI-focused software engineering.
• Strong proficiency in Python programming.
• Hands-on knowledge of machine learning and deep learning theories and frameworks.
• Proven experience in developing and deploying generative AI or large language model (LLM) applications.
• Practical know-how of RAG architectures design and implementation.
• Familiarity with embeddings, vector databases, semantic search, and retrieval pipelines.
• Experience integrating AI and machine learning models into applications using APIs.
• Solid understanding of software engineering fundamentals, data structures, algorithms, API design, and system architecture.
• Experience using Git and modern software development workflows.
• Excellent analytical, problem-solving, and troubleshooting skills.
• Ability to clearly explain technical concepts to technical and non-technical audiences alike.

Preferred Technical Skills

• Frameworks: PyTorch, TensorFlow, scikit-learn.
• Natural language processing and deep learning expertise.
• Familiarity with Hugging Face Transformers library.
• Experience with model evaluation, monitoring, optimization, fine-tuning, and inference enhancement.
• Exposure to LLM platforms such as OpenAI, Azure OpenAI, Anthropic.
• Use of advanced frameworks like LangChain, LangGraph, or LlamaIndex.
• Prompt engineering and structured output generation techniques.
• Building AI agents including function calling and tool integration.
• Evaluation and establishment of guardrails for LLMs.
• Experience in Arabic natural language processing, Arabic-language models, or multilingual AI solutions.
• Data and search technologies: SQL, PostgreSQL, vector databases like Pinecone, Qdrant, Weaviate, Milvus, Chroma, Elasticsearch, OpenSearch.
• API development with REST and FastAPI.
• Data processing for documents, text, and unstructured information.
• Cloud platforms: Microsoft Azure, AWS, or Google Cloud.
• Use of Docker and containerization technologies.
• Implementation of CI/CD pipelines; familiarity with Kubernetes is a plus.
• Expertise in logging, monitoring, observability, and production support.

Key Competencies and Personal Attributes

• A strong business mindset aimed at achieving measurable results.
• Ability to convert business objectives into viable, scalable AI solutions.
• Driven ownership disposition leading projects from concept through deployment.
• Effective communication and collaboration skills across diverse teams.
• Capability to work independently while fostering a cooperative engineering environment.
• Curiosity and eagerness to quickly adapt within the fast-evolving AI field.
• A commitment to high standards encompassing quality, security, privacy, and ethical AI use.

Preferred Profile

The ideal candidate possesses 4–6 years of relevant AI engineering experience including the creation of production-ready machine learning or generative AI systems. Particular preference is given to applicants with background in Arabic-language data handling, Arabic natural language processing, multilingual model expertise, or AI products serving Arabic-speaking users. Arabic language skills are an advantage but evaluated strictly for job-relevance and not as a nationality condition. Candidates must be proficient in English for professional and technical communication.