AI Agent Engineer

2 days ago

Riyadh, Ar Riyāḑ, Saudi Arabia Lucidya Full time

AI & Agent Development

  • Design, develop, and optimize machine learning and deep learning models for AI agent use cases.
  • Build intelligent systems capable of reasoning, prediction, automation, and decision support.
  • Apply NLP, data analysis, and agentic workflows to solve complex CX and operational challenges.

Data & Model Engineering

  • Manage, clean, and preprocess large datasets to extract meaningful features.
  • Train, evaluate, and fine-tune machine learning models to meet performance and reliability standards.
  • Continuously monitor and improve model accuracy, robustness, and efficiency.

Production & Scalability

  • Deploy AI models into production environments with a focus on scalability, performance, and reliability.
  • Collaborate on MLOps practices to support continuous integration, monitoring, and improvement.
  • Ensure AI systems integrate smoothly with existing platforms and workflows.

Cross-Functional Collaboration

  • Work closely with data scientists, software engineers, product managers, and domain experts.
  • Translate business problems into effective AI solutions with measurable outcomes.
  • Contribute to solution design for enterprise pilots and long-term deployments.

Governance & Quality

  • Ensure AI solutions comply with ethical standards, data privacy requirements, and legal regulations.
  • Document models, algorithms, workflows, and decisions clearly for internal and external stakeholders.
  • Stay up to date with the latest AI research, tools, and best practices; and apply them where valuable.
Desired Candidate Profile

Technical Skills

  • 2+ years of hands-on experience building and deploying AI-driven systems, with a strong focus on AI agents or agentic workflows, and demonstrated impact on real business outcomes (e.g. automation, efficiency gains, cost reduction, CX improvement).
  • Strong programming skills in Python (Java is a plus).
  • Hands-on experience with machine learning and deep learning techniques.
  • Practical experience using TensorFlow, PyTorch, or similar frameworks.
  • Solid understanding of data preprocessing, feature engineering, model training, and evaluation.
  • Experience deploying AI models into production or production-like environments.

Problem-Solving & Mindset

  • Ability to analyze complex problems and design innovative AI-driven solutions.
  • Strong systems thinking, understanding how models behave in real-world environments.
  • Curiosity and commitment to continuous learning in a fast-evolving AI landscape.

Collaboration & Communication

  • Comfortable working in cross-functional, product-driven teams.
  • Able to clearly document and explain technical concepts to diverse stakeholders.

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