Position Title : AI/ML Engineer – Agentic AIExperience Required: 4–6 Years (Should be open to Travel)
Employment Type : Full-Time - Riyadh - Onsite
Job Overview
We are seeking a highly skilled AI/ML Engineer with hands-on experience in building intelligent AI systems, machine learning models, and Agentic AI solutions. The ideal candidate will have strong expertise in designing, developing, and deploying AI-powered applications leveraging LLMs, autonomous agents, orchestration frameworks, and modern ML techniques.
The role requires a strong engineering mindset, practical AI implementation experience, and the ability to work across the full AI/ML lifecycle from experimentation to production deployment.
Key Responsibilities-
Design, develop, and deploy AI/ML solutions for real-world business use cases.
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Build and optimize Agentic AI systems using LLMs, autonomous workflows, and multi-agent architectures.
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Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks.
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Work with orchestration frameworks such as LangChain, CrewAI, AutoGen, LangGraph, or similar technologies.
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Integrate AI agents with APIs, databases, enterprise systems, and third-party tools.
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Fine-tune, evaluate, and optimize Large Language Models (LLMs).
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Develop Retrieval-Augmented Generation (RAG) pipelines and vector search implementations.
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Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions.
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Perform prompt engineering, model experimentation, and performance optimization.
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Ensure AI solutions are production-ready, scalable, secure, and cost-efficient.
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Monitor model performance, drift, and continuous improvement processes.
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Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies.
Required Skills & Expertise-
Strong hands-on experience in Machine Learning, Generative AI, and Agentic AI development.
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Proficiency in Python and AI/ML development frameworks.
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Experience with:
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LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks
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OpenAI, Anthropic, Gemini, or open-source LLMs
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RAG architectures and Vector Databases
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Prompt Engineering & AI workflow automation
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Solid understanding of:
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NLP concepts
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ML algorithms and model evaluation
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Deep Learning fundamentals
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AI model deployment and inference optimization
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Experience with ML libraries/frameworks such as:
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PyTorch
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TensorFlow
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Scikit-learn
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Hugging Face Transformers
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Experience with cloud platforms such as Azure, AWS, or GCP is preferred.
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Familiarity with Docker, APIs, CI/CD, and MLOps practices.
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Strong problem-solving and analytical skills.
Preferred Qualifications-
Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
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Experience working on enterprise AI automation or AI assistant platforms is highly preferred.
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Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus.
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