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Agentic AI Engineer

πŸ“… May 14
PythonLangchainCrewaiFunction Calling
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πŸ“œ Description

  • Architect agent loops for planning, memory, retrieval, tool use, and self-verification.
  • Implement tools and MCP-style interfaces using functions, APIs, database queries, and files.
  • Combine RAG with agents through chunking, embeddings, retrieval, reranking, and grounding.
  • Add safety guardrails, including execution sandboxes, permissions, rate limits, and PII policies.
  • Evaluate agent task success, autonomy depth, and recovery rate.
  • Optimize agent reliability, determinism, and cost.

πŸ› οΈ 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).
Full job description

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 , webook.com 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.

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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