Agentic AI, Engineer

Master Works; Riyadh; On-site; SAR 300,000 - 540,000; Full time

Job summary

Master Works is seeking an Agentic AI Engineer to design, build, and deploy agentic AI systems capable of planning, reasoning, and acting across single- and multi-agent workflows. The role focuses on RAG, memory, tool calling, inter-agent communication, and human-in-the-loop controls.

You will collaborate with Generative AI engineers, application engineers, and product teams to bring prototypes to production, ensuring safe, reliable, and high-quality AI experiences for customers.

Qualifications

• Bachelor's or Master's in CS/AI/ML or related field.
• 2+ years hands-on experience building agentic AI systems.
• Prefer 5+ years software engineering experience.
• Experience with cloud platforms (AWS/Azure/GCP) and microservices.
• Experience with AI safety, observability, explainability.

Responsibilities

• Architect, build, and deploy agentic AI systems integrating AI agents with models, tools, and APIs.
• Develop RAG, memory, and reasoning pipelines grounding decisions in real data.
• Design single-agent and multi-agent workflows including tool selection and inter-agent communication.
• Optimize orchestration and reasoning for performance, cost, and reliability.
• Collaborate with Generative AI, application, MLOps, and product teams to move prototypes to production.
• Monitor AI systems for safety, accuracy, and user experience.
• Document architectures, guardrails, and context-engineering strategies for reproducibility.

Skills

Hands-on AI/ML development

Software engineering

MLOps

Inter-agent communication

Education

Bachelor's or Master's in Computer Science/AI/ML

Tools

Kubernetes

Docker

CI/CD pipelines

LLM frameworks

Job description

Master Works is looking for an Agentic AI, Engineer to join our growing team and design, build, and deploy agentic AI systems that can plan, reason, and act. The role covers both single-agent and multi-agent systems, as well as orchestration of workflows involving retrieval-augmented generation (RAG), context engineering, reasoning, tool calling, memory, and inter-agent communication. This role is ideal for a strong software engineer with hands-on AI/ML development experience and a passion for transforming generative AI models into reliable, goal-driven systems capable of solving complex, real-world business problems.

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-built 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

Requirements

• 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
• 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

Job Location:

HQ