Prompt Engineer (LLM Systems, Evals & Safety) at Supertech Group

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. webook.com 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

Design high-quality prompts, system instructions, and tooling that make our LLM features accurate, safe, and cost-effective. You’ll own evaluation, prompt versioning, and continuous improvement.

Key Responsibilities:

• Author, refactor, and chain prompts (system/tool/policy) for varied tasks.
• Create offline/online evaluation harnesses (rubrics, golden sets, metrics).
• Build prompt libraries with versioning, A/B testing, and telemetry.
• Reduce hallucinations via verification, constrained decoding, and tool use.
• Implement safety: jailbreak/prompt-injection tests, content policy checks, PII handling.
• Partner with engineers to integrate prompts into production features.

Requirements

Requirements

• Demonstrated prompt design across multiple task types and models.
• Experience building eval datasets and automated scoring (e.g., accuracy, faithfulness, utility, cost/latency).
• Familiarity with retrieval-augmented generation concepts and tool/function calling.
• Strong scripting (Python/TypeScript) for data prep, evals, and analysis.
• Clear writing; ability to translate business goals into measurable prompt specs.

Nice-to-Haves

• Experience with LangChain/LLM orchestration, vector stores, and rerankers.
• Knowledge of safety tooling and red-teaming techniques.
• Experiment platforms (feature flags, A/B tests), analytics.