Business Support System Specialist

Zoomlion Gulf FZE; Dubai; On-site; AED 180,000 - 240,000; Full time

Job summary

Zoomlion Gulf FZE in Dubai hires an AI prompts engineer to design and refine prompts and system instructions for our AI assistant. You translate business rules into reliable prompts, structure outputs, and collaborate with engineers on tooling integration.

You prepare knowledge sources, build evaluation sets, and monitor performance across languages, ensuring responsible-use practices and clear documentation.

Qualifications

• Bachelor's degree or related field required.
• 1–3 years of experience with LLMs or AI services.
• Proven prompt engineering experience with commercial LLMs.
• Understanding of tokens, context windows, embeddings and hallucinations.
• Experience reading/writing code to call APIs and process JSON.

Responsibilities

• Design, write and iterate prompts and system instructions for the AI assistant.
• Translate business rules into instructions and constraints for the model.
• Define and maintain the assistant's tools and usage rules with engineers.
• Prepare knowledge sources: collect, clean, chunk and structure material.
• Build evaluation sets and report accuracy, regressions with evidence.
• Tune speech and visual recognition for real user input and accents.
• Investigate AI failures and trace causes in prompts or tools.
• Monitor token usage, latency and cost; suggest optimizations.
• Test the assistant across languages and ensure correct responses.
• Write documentation of capabilities and limits for users.

Skills

Prompt engineering

LLM behavior knowledge

API usage & JSON processing

Test case design

English communication

Education

Bachelor's degree in Computer Science or related field

Tools

Python

JavaScript/TypeScript

Git

API integration

Job description

Technology You Will Work With:

• Large language models consumed through APIs (Alibaba Qwen / Model Studio, Anthropic Claude, OpenAI and comparable providers).
• Prompt engineering, system instructions, structured (JSON) outputs and tool / function calling.
• Retrieval-augmented generation: embeddings, chunking and vector search.
• Speech-to-text, text-to-speech and image and document recognition (OCR) services.
• Python or TypeScript for the scripts, integrations and evaluations you write.
• Evaluation, prompt versioning and observability tooling, with Git and GitHub for review and history.

Key Responsibilities:

• Design, write and iterate on the prompts and system instructions that drive the product's AI assistant, and version them the way code is versioned.
• Turn business rules and operating procedures into instructions, examples and constraints that a model follows reliably.
• Define and maintain the assistant's tools - what each one does, the arguments it takes and when the model should reach for it - working with engineers on the implementation.
• Prepare the knowledge the assistant reads: collect, clean, chunk and structure source material, and keep it current as the business changes.
• Build evaluation sets for every AI feature, run them on each change, and report accuracy, regressions and failure patterns with evidence rather than impressions.
• Integrate and tune speech recognition and image or document recognition so they hold up on real user input, including accented speech and poor-quality photographs.
• Investigate reported AI failures - a wrong answer, an invented fact, a missed or mis-called tool - and trace each one to its cause in the prompt, the retrieved data or the tool definition.
• Monitor token usage, latency and cost per request, and propose changes that reduce them without weakening quality.
• Test the assistant across the languages it serves and confirm it answers correctly in each of them.
• Apply responsible-use practice: keep sensitive data out of prompts and logs, and flag outputs that should never be produced.
• Write clear documentation of what the assistant can and cannot do, and update the in-app user manual whenever your change alters what a user sees or gets.

Requirements:

• Bachelor's Degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Engineering, or a related field.
• 1-3 years of experience building with large language models or other AI services. Internships and substantial personal or open-source AI projects will be considered.
• Demonstrable prompt engineering experience with a commercial LLM, and the judgement to explain why one prompt outperforms another.
• Working understanding of how these models behave: tokens and context windows, temperature, embeddings, structured output, and the common causes of hallucination.
• Comfortable reading and writing code to call APIs and process JSON - Python or JavaScript / TypeScript is sufficient; you do not need to be a full-stack engineer.
• Able to design test cases and evaluate model output objectively against them.
• Familiarity with structured data: JSON, CSV and basic SQL.
• Comfortable with Git and a pull-request based workflow.
• Strong analytical, problem-solving and communication skills, with attention to detail.
• Excellent command of written and spoken English.