Agentic AI Engineer📣 Job Ad

11 minutes ago

	Contract Type	Full-time
	Workplace type	On-site
	Location	Saudi Arabia

Job Description

About the Role

Master-Works is seeking an Agentic AI Engineer to join its growing team. This full-time position involves designing, building, and deploying agentic AI systems capable of planning, reasoning, and acting. The role focuses on transforming generative AI models into reliable, goal-driven systems that solve complex, real-world business problems.

Role Overview

The Agentic AI Engineer will work with both single-agent and multi-agent systems. This includes orchestrating workflows that incorporate retrieval-augmented generation (RAG), context engineering, reasoning, tool calling, memory, and inter-agent communication. This position is ideal for a strong software engineer with hands-on AI/ML development experience and a passion for advanced AI solutions.

Key Responsibilities

Architect, build, and deploy agentic AI systems that integrate AI agents with foundation models, enterprise systems, third-party tools, and APIs using established agentic frameworks or custom orchestrators.
Build and maintain retrieval-augmented generation (RAG), memory, and reasoning pipelines that ground agent decisions in reliable, real-world data and enable persistent, contextual, and adaptive behavior.
Design single-agent and multi-agent workflows, including planning, delegation, tool selection, handoffs, inter-agent communication, and human-in-the-loop controls.
Optimize orchestration and reasoning performance while balancing autonomy, latency, cost, interpretability, reliability, and maintainability.
Collaborate with Generative AI engineers, application engineers, MLOps engineers, and product teams to move agentic AI solutions from prototype to production.
Monitor, evaluate, and benchmark agent performance, and help ensure AI systems are safe, accurate, trustworthy, observable, and capable of delivering a high-quality user experience.
Document agent architectures, communication flows, guardrails, context-engineering strategies, memory design, tool interfaces, and orchestration logic to ensure clarity and reproducibility.
Stay current with advances in agentic AI, multi-agent orchestration, RAG, model-context protocols, cognitive architectures, evaluation methods, and AI safety mechanisms.
Collaborate with cross-functional teams to design and deliver complete AI solutions for customers.

Qualifications and Experience

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field.
2+ years of hands-on experience developing agentic AI systems, LLM-powered applications, or advanced Generative AI solutions.
Preferably 5+ years of overall professional software engineering experience.
Contributions to open-source agentic AI frameworks, orchestration platforms, evaluation tooling, or agent communication protocols.

Required Technical Expertise

Experience building microservices and deploying AI applications on cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Experience with AI safety, guardrails, observability, traceability, evaluation, and explainability for agentic AI systems.
Experience deploying LLM or agentic workloads in production using containers, Kubernetes, CI/CD pipelines, and modern MLOps or LLMOps practices.