Agentic AI Engineer

2 days ago

Amman, Amman, Jordan Supertech Group Full time 60,000 - 120,000 per year

Do you want to love what you do at work? Do you want to make a difference, an impact, and transform peoples lives? Do you want to work with a team that believes in disrupting the normal, boring, and average?

If yes, then this is the job you are looking for ,  is Saudi's #1 event ticketing and experience booking platform in terms of technology, features, agility, revenue serving some of the largest mega events in the Kingdom surpassing over 2 billion in sales.   is part of the Supertech Group also consisting of UXBERT Labs, one of the best digital and user experience design agencies in the GCC, along with Kafu Games, the largest esports tournament platform in MENA. 

Role Overview

Build multi-step, tool-using agents that plan, retrieve, act, and verify. You'll design agent architectures, integrate tools/APIs, and deliver robust execution with safety and observability.

Key Responsibilities:

  • Architect agent loops (planning, memory, retrieval, tool use, self-verification).
  • Implement tools (functions/APIs/DB queries/files) and MCP-style interfaces.
  • Combine RAG with agents: chunking, embeddings, retrieval, reranking, grounding.
  • Add guardrails: execution sandboxes, permissions, rate limits, PII policies.
  • Build evaluation for agents (task success, autonomy depth, recovery rate).
  • Optimize for reliability, determinism where needed, and cost.

Requirements

  • Production experience with LangChain/CrewAI (or similar) and function/tool calling.
  • Strong Python engineering; async patterns; robust error handling.
  • Practical RAG skills: vector DBs, indexing pipelines, and retrieval quality tuning.
  • Systems thinking: queues, retries, idempotency, caching, concurrency control.
  • Security & safety for agents (prompt injection, tool scoping, least privilege).
Nice-to-Haves
  • GCP/AWS, Docker/Kubernetes; message buses/streams.
  • LLM evaluation frameworks; synthetic data generation.
  • Graph-based planning, constraint solvers, or program-of-thought techniques.

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