
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,…
What they do: AI voice orchestration platform for building, testing, and deploying voice agents (phone and web/in-app)
Founded: June 1, 2022 (listed)
Headquarters: Washington, District of Columbia, United States
Employees: 58 (reported)
Recent funding: Seed round announced Jan 22, 2025
Enterprise conversational AI / voice agent orchestration for large-scale call volumes and complex workflows
2022
Artificial Intelligence / Voice Technology
Seed round announced Jan 22, 2025; reported investors include F6 Ventures and Ibtikar Fund
Reported Aug 2023 seed entry (Dealroom listing Ibtikar Fund)
2022 non-equity assistance entry reported in company record
“Ibtikar Fund and F6 Ventures listed as investors”
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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.