About the role

Be part of shaping how AI transforms how we work. You’ll scout emerging AI technologies, pilot new tools, and coordinate cross-departmental adoption projects. A key focus will be managing and enhancing our internal Knowledge Hub — ensuring information flows seamlessly and employees can leverage AI to its fullest. - Design and implement agentic architectures — multi-step planners, ReAct loops, tool-use orchestration, and memory systems - Build reliable agent pipelines that handle ambiguity, recover from failures, and know when to escalate to humans - Integrate LLMs (Claude, GPT, open-source models) with external tools, APIs, databases, and enterprise systems - Develop evaluation frameworks to measure agent reliability, accuracy, cost, and latency in production - Implement guardrails, safety layers, and human-in-the-loop controls for autonomous systems - Optimize for real-world constraints: token costs, latency budgets, rate limits, and context window management - Collaborate with product and engineering teams to identify high-value automation opportunities across the digital entertainment portfolio - Contribute to internal tooling and frameworks that accelerate agent development across the organization

Requirements

- 5+ years of software engineering experience, with at least 1-2 years focused on LLM-based systems

- Hands-on experience building agentic systems — not just prompt engineering, but orchestration, tool use, and state management

- Strong proficiency in Python; familiarity with TypeScript is a plus

- Deep understanding of LLM APIs (Claude, OpenAI, etc.), including function calling, structured outputs, and streaming

- Experience with at least one agent framework (LangGraph, CrewAI, AutoGen, custom frameworks)

- Solid software engineering fundamentals: testing, CI/CD, observability, version control

- Experience with RAG pipelines, vector databases (Pinecone, Weaviate, pgvector), and retrieval systems

- Experience with MCP (Model Context Protocol) or similar tool-integration standards

Responsibilities

Design and implement agentic architectures — multi-step planners, ReAct loops, tool-use orchestration, and memory systems

Build reliable agent pipelines that handle ambiguity, recover from failures, and know when to escalate to humans

Integrate LLMs (Claude, GPT, open-source models) with external tools, APIs, databases, and enterprise systems

Develop evaluation frameworks to measure agent reliability, accuracy, cost, and latency in production

Implement guardrails, safety layers, and human-in-the-loop controls for autonomous systems

Optimize for real-world constraints: token costs, latency budgets, rate limits, and context window management

Collaborate with product and engineering teams to identify high-value automation opportunities across the digital entertainment portfolio

Contribute to internal tooling and frameworks that accelerate agent development across the organization

Skills

Python

TypeScript (familiarity)

LLM APIs (Claude, OpenAI, etc.)

function calling

structured outputs

streaming

agent frameworks (LangGraph, CrewAI, AutoGen, or similar)

RAG pipelines

vector databases (Pinecone, Weaviate, pgvector)

retrieval systems

software engineering fundamentals (testing, CI/CD, observability, version control)

state management

tool orchestration

Agentic AI Agent

About the role

Requirements

Responsibilities

Skills

Similar jobs across the Gulf