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QuantumLoopAI

AI receptionist for NHS primary care

AI/ML & Prompt Engineer LLM - RAG & Voice Agent

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeRemote in India

About the Job

Requirements

  • Demonstrable hands-on experience with prompt engineering, large language models such as GPT, LLaMA, or Mistral, retrieval-augmented generation frameworks, and voice-agent or dialogue-system design, with shipped projects or open-source contributions.
  • Advanced proficiency in Python for machine-learning and artificial-intelligence development.
  • Experience building application programming interfaces in NestJS and familiarity with Next.js and React for frontend integration.
  • Strong understanding of Azure services, including App Services, Functions, and Cognitive Services; containerisation with Docker; and relational databases such as MySQL.
  • Experience designing microservices, distributed architectures, and RESTful or GraphQL APIs.
  • Excellent written and verbal communication skills and the ability to articulate complex AI and voice-agent concepts to technical and non-technical stakeholders.
  • Comfort working remotely and collaborating asynchronously with a UK-based team during UK business hours, 9:00 AM to 6:00 PM GMT/BST.

Responsibilities

  • Architect and deploy LLM- and RAG-based systems that ingest data sources, generate accurate responses, and power chatbot and voice-agent interactions.
  • Design, iterate, and optimise prompts and voice-agent dialogue flows to maximise response relevance, reduce latency, and ensure clinical safety across text and voice channels.
  • Partner with frontend teams using Next.js and React and backend teams using NestJS and Python to integrate AI and voice-agent components into the Azure-hosted microservices architecture.
  • Instrument AI and voice-agent pipelines, analyse logs and user feedback, troubleshoot edge cases, and implement continuous-learning improvements.
  • Stay current with advances in LLMs, RAG, conversational AI frameworks, GDPR, and DTAC to inform the technical roadmap.
  • Define and execute rigorous test plans with QA to validate model accuracy, voice-agent performance, and compliance with healthcare standards.
  • Mentor junior engineers and advocate for best practices in MLOps, prompt engineering, voice-agent design, and model governance.

Desired Qualifications

  • Contributions to open-source LLM or RAG tooling.
  • Experience with MLOps pipelines, model monitoring, and automated evaluation frameworks.
  • Background in speech-to-text, text-to-speech, or telephony integration.

About the Company

QuantumLoopAI

AI receptionist for NHS primary care

EMMA by QuantumLoopAI is an AI receptionist designed for NHS primary care. It answers patient calls during GP surgery hours instantly, with no queue or hold music. EMMA handles both clinical and administrative inquiries, triages to the right outcome, and integrates with NHS tools like Accurx. It is used across hundreds of GP surgeries and PCNs, serving over 2 million NHS patients. This reduces call-handling costs (up to about 80%) and improves patient access and satisfaction, while easing pressure on reception staff. QuantumLoopAI emphasizes NHS clinical safety, DTAC certification, and alignment with NHS standards. The company’s goal is to make primary care more accessible, efficient, and sustainable by eliminating phone bottlenecks and letting reception teams focus on in-person patient care.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
London, United Kingdom
Founded
2023

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