Agentic AI Agent

Mondia; Dubai; Presencial; AED 180 000 - 240 000; Tempo integral

Resumo da oferta

Mondia is advancing AI-driven automation and knowledge management. The role focuses on designing agentic architectures, orchestrating tools, and integrating LLMs with enterprise systems to empower employees across the organization.

You will build scalable agent pipelines, measure performance, and implement guardrails while collaborating with product and engineering teams to identify high-value automation opportunities in the digital entertainment portfolio.

Qualificações

• 5+ years of software engineering experience, with at least 1-2 years focused on LLM-based systems.
• Hands-on experience building agentic systems — 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.

Responsabilidades

• 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 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 token costs, latency budgets, rate limits, and context window management.
• Collaborate with product and engineering teams to identify high-value automation opportunities across the portfolio.
• Contribute to internal tooling and frameworks that accelerate agent development.

Conhecimentos

Python

LLM-based systems

Agent orchestration

Testing

CI/CD

Observability

Version control

Retrieval systems

Ferramentas

LangGraph

CrewAI

AutoGen

Pinecone

Weaviate

pgvector

MCP

Descrição da oferta de emprego

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 escal ate 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