
DataQueue empowers enterprises to build, test, and deploy intelligent AI voice agents with unparalleled performance. Whether you’re building a voice product or trying to handle millions of calls,…

DataQueue empowers enterprises to build, test, and deploy intelligent AI voice agents with unparalleled performance. Whether you’re building a voice product or trying to handle millions of calls,…
Product: VoiceHub — enterprise AI voice agent platform for orchestration, deployment, and management of AI conversations
Tech strengths: Multi-model selection (STT, LLM, TTS), voice-native streaming, visual flow builder and prompt-based modes
Use cases / focus: Call handling (inbound/outbound), speech analytics, QA/testing, white-label voice products; MENA/Arabic localization noted
Headcount: 84 (reported)
Funding: Seed round closed Jan 22, 2025; reported investors include Ibtikar Fund and F6 Ventures
Enterprise conversational AI and voice orchestration for customer-facing and internal voice workflows
2022
Artificial intelligence / Conversational AI / Speech analytics
Profiles report a Seed round closed Jan 22, 2025; investors listed include Ibtikar Fund and F6 Ventures
“Ibtikar Fund and F6 Ventures listed among investors”
| Company |
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DataQueue is looking for a motivated Prompt Engineering Intern
who is passionate about Artificial Intelligence, especially Large Language Models (LLMs), Agentic Workflows, and real-world communication integrations.
As an intern, you will work closely with our engineering team to build, test, and improve AI agents within our Voicehub
platform that power automated telephone, messaging, and scheduling systems.
Responsibilities
Agent Construction:
Assist in designing and refining prompt logic for our proprietary LLMs within Voicehub to handle complex conversation decision points.
Omnichannel Integration:
Build and test agent workflows that connect across Telephone
, SMS
, and Email
.
Tool-Use Implementation:
Integrate external services like Google Calendar
and Airtable
into agent logic via REST APIs
.
Pipeline Development:
Contribute to building and maintaining automation pipelines and "connective tissue" using n8n
.
Performance Testing:
Test and benchmark agents for accuracy, reliability, and proper handling of structured JSON outputs.
Continuous Learning:
Stay updated with the latest advancements in prompt engineering, context management, and agentic frameworks.
Requirements
Nice-to-Have Skills
Experience with automation platforms like n8n
, Make, or Zapier.
Familiarity with Airtable
for managing structured data and agent memory.
Exposure to Google Calendar API
or other productivity tool integrations.
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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
(knowing how temperature, system instructions, and context windows affect model behavior).
Familiarity with Python
and handling JSON
data structures.
Knowledge of REST APIs
(the ability to read documentation and perform GET/POST requests).
Basic understanding of NLP concepts (tokenization, embeddings, and transformers).
Personal or academic projects involving LLM prompting, automation, or building functional AI agents.
Interest in telephony systems or voice-based AI interactions.