AI​/ML Engineer – Agentic AI

AI/ML Engineer – Agentic AI

Experience

Required:

4–6 Years (Should be open to Travel)

Employment Type:

Full-Time – Riyadh – Onsite

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.

• Design, develop, and deploy AI/ML solutions for real‑world business use cases.
• Build and optimize Agentic AI systems using LLMs, autonomous workflows, and multi‑agent architectures.
• Develop machine learning models for prediction, classification, recommendation, NLP, and automation tasks.
• Work with orchestration frameworks such as Lang Chain, CrewAI, Auto Gen, Lang Graph, or similar technologies.
• Integrate AI agents with APIs, databases, enterprise systems, and third‑party tools.
• Fine‑tune, evaluate, and optimize Large Language Models (LLMs).
• Develop Retrieval‑Augmented Generation (RAG) pipelines and vector search implementations.
• Collaborate with data engineers, software developers, and product teams to deliver scalable AI solutions.
• Perform prompt engineering, model experimentation, and performance optimization.
• Ensure AI solutions are production‑ready, scalable, secure, and cost‑efficient.
• Monitor model performance, drift, and continuous improvement processes.
• Stay updated with emerging AI, Generative AI, and Agentic AI trends and technologies.

• Strong hands‑on experience in Machine Learning, Generative AI, and Agentic AI development
  .
• Proficiency in Python and AI/ML development frameworks.
• Experience with:
  • Lang Chain, Lang Graph, CrewAI, Auto Gen, or similar frameworks
  • OpenAI, Anthropic, Gemini, or open‑source LLMs
  • RAG architectures and Vector Databases
  • Prompt Engineering & AI workflow automation
• Solid understanding of:
  • NLP concepts
  • ML algorithms and model evaluation
  • Deep Learning fundamentals
  • AI model deployment and inference optimization
• Experience with ML libraries/frameworks such as:
  • Py Torch
  • Tensor Flow
  • Scikit‑learn
  • Hugging Face Transformers
• Experience with cloud platforms such as Azure, AWS, or GCP is preferred.
• Familiarity with Docker, APIs, CI/CD, and MLOps practices.
• Strong problem‑solving and analytical skills.

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.
• Experience working on enterprise AI automation or AI assistant platforms is highly preferred.
• Exposure to AI governance, evaluation frameworks, and AI observability tools is a plus.