Prompt Engineering Intern

DataQueue is the largest and fastest-growing Voice AI company in the MENA region, deploying AI voice agents across banks, telecoms, and governments — and scaling rapidly.

VoiceHub, our platform, enables businesses to design, test, and deploy AI voice agents at scale, combining LLMs with a full voice stack including TTS, STT, copilots, speech analytics, and real-time workflows across 25+ languages.

We are looking for a** Prompt Engineering Intern** who is excited about building real AI systems and understands that AI behavior does not stop at text. In this role, you will work closely with our engineering team to build, test, and improve AI agents within VoiceHub, where prompt design, model behavior, speech delivery, and workflow logic must all work together to create reliable and natural interactions.

Responsibilities

• Agent Construction: Assist in designing and refining prompt logic for our proprietary LLMs within VoiceHub to handle complex conversational flows and decision points.
• Voice Agent Design: Help structure responses that are not only correct for the LLM, but also clear for users, natural when spoken, and suitable for downstream voice systems such as TTS.
• Omnichannel Integration: Build and test agent workflows that connect across Telephone, WhatsApp, SMS, and Email.
• Tool-Use Implementation: Integrate external services such as Google Calendar and Airtable into agent logic via REST APIs.
• Pipeline Development: Contribute to building and maintaining automation pipelines and orchestration layers using tools such as n8n.
• Performance Testing: Test and benchmark agents for accuracy, reliability, latency, structured JSON outputs, and real conversational performance.
• Behavior Optimization: Help improve how agents behave across multi-turn conversations, real-time constraints, and voice interaction patterns.
• Continuous Learning: Stay updated with the latest advancements in prompt engineering, context management, agentic workflows, and voice AI systems.

Requirements

• Currently pursuing or recently completed a Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
• Strong understanding of LLM fundamentals, including how temperature, system instructions, and context windows affect model behavior
• Familiarity with Python and handling JSON data structures
• Knowledge of REST APIs, including the ability to read documentation and perform GET/POST requests
• Basic understanding of NLP concepts such as tokenization, embeddings, and transformers
• Personal or academic projects involving LLM prompting, automation, or building functional AI agents
• Ability to think beyond text and consider how outputs behave in real conversational and voice-based systems

Strong Signal

• We would be especially interested in candidates who have already:
• Built conversational agents, chatbots, or automation systems
• Worked with LLM APIs in practical projects
• Designed prompts that produce reliable and structured outputs
• Worked with TTS systems, speech-based interfaces, or voice technologies
• Thought about how phrasing, formatting, and punctuation affect spoken output
• Optimized AI responses for real-time interaction
• Approached problems as systems involving LLMs, speech, and workflow logic rather than isolated prompts
• Experience with automation platforms such as n8n, Make, or Zapier
• Familiarity with Airtable for managing structured data and agent memory

Nice-to-Have Skills

Familiarity with telephony systems, streaming pipelines, or voice-based AI interactions

Why Join DataQueue

• Work with one of the fastest-growing AI companies in the MENA region
• Build systems that solve real problems for enterprises at scale
• Join our vision to become the voice infrastructure of the region
• Work on production systems across LLMs, voice technologies, and real-time workflows
• Be part of a team that moves fast, builds seriously, and operates with high standards

This Role Is Not For You If

• You only think in terms of text prompts
• You have only experimented casually with AI tools without building systems
• You are looking to learn AI entirely from scratch