Agentic AI Engineer
webook.com · Remote · Location not stated
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First recorded by Psst: 3 November 2026. Sign in with Google to continue to the employer. A free account is enough.
The 20-second read
- Experience
- Experience not stated
- Where you can live
- Location not stated
- Skills and tools
- python, aws, gcp, docker, kubernetes, ticketing
- Job type
- Full-time
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Job details
- Where you can work
- Location not stated
- Employment type
- Full-time
- Advertised pay
- Not stated by the employer
- Experience
- Experience not stated
- Employer publication date
- 14 May 2026
- First recorded by Psst
- 3 November 2026
- Last checked at the source
- 3 November 2026
About the job
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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- Open 6 months
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