Prompt & AI / ML Engineer – Chatbot LLM & RAG

About the job

Overview At QuantumLoopAI, we’re redefining customer engagement in healthcare with EMMA, the UK’s leading AI receptionist for GP practices. By combining cutting-edge Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), advanced prompt engineering, and our bespoke voice agent technology, we eliminate phone queues, accelerate call handling, and enhance patient access—transforming the primary care experience end-to-end. As our Senior Prompt & AI / ML Engineer, you will drive the design, development and deployment of the AI models that power EMMA’s intelligent chatbots, voice agent and telephony services. You’ll collaborate closely across product, engineering and clinical teams to deliver data-driven improvements, ensuring our solutions remain at the forefront of NHS digital transformation. Responsibilities • Architect & Deploy AI Models : Lead the end-to-end development of LLM- and RAG-based systems to ingest NHS data sources, generate accurate responses, and power both chatbot and voice agent interactions. • Prompt & Voice Agent Engineering : Craft, iterate and optimise prompts—and design voice-agent dialogue flows—to maximise response relevance, reduce latency and ensure clinical safety across text and voice channels. • Cross-Functional Collaboration : Partner with frontend (Next.js, React) and backend (NestJS, Python) teams to integrate AI and voice agent components into our Azure-hosted microservices architecture. • Performance Monitoring & Optimisation : Instrument AI and voice-agent pipelines, analyze logs and user feedback, troubleshoot edge cases, and implement continuous-learning improvements. • Innovation & R&D : Stay abreast of the latest advances in LLMs, RAG, conversational AI frameworks, and NHS-specific compliance (GDPR, DTAC) to inform our technical roadmap. • Testing & Validation : Define and execute rigorous test plans in collaboration with QA to validate model accuracy, voice-agent performance and compliance with healthcare standards. • Technical Leadership : Mentor junior engineers, advocate for best practices in MLOps, prompt engineering, voice-agent design, and model governance, and contribute to architecture reviews. What You’ll Bring • Proven Expertise : Hands-on experience with prompt engineering, LLMs (e.g., GPT, Bloom, LLaMA), RAG frameworks, and voice-agent / dialogue-system design, with demonstrable projects or open-source contributions. • Programming Skills : Advanced proficiency in Python; comfortable building APIs in NestJS; familiarity with Next.js / React for frontend integration. • Cloud & Data : Strong understanding of Azure services (App Services, Functions, Cognitive Services), containerisation (Docker), and relational databases (MySQL). • Systems Thinking : Experience designing microservices, distributed architectures and RESTful / GraphQL APIs. • Domain Interest : A passion for healthcare technology, patient-centric design and improving NHS primary care workflows. • Communication : Excellent written and verbal skills to articulate complex AI and voice-agent concepts to technical and non-technical stakeholders. • Collaboration : A proactive, team-oriented mindset and a drive to mentor peers and contribute to a continuous-learning culture.

Requirements

• AI Models
• Prompt Engineering
• Voice Agent Engineering
• Collaboration
• Azure Services
• Python
• Frontend Integration

Qualifications

• Hands-on experience with prompt engineering
• Proficiency in Python
• Strong understanding of Azure services
• Experience designing microservices

Preferred Technologies

• AI Models
• Prompt Engineering
• Voice Agent Engineering
• Collaboration
• Azure Services
• Python
• Frontend Integration

Benefits

• Impactful Work
• Innovative Environment
• Flexible Hybrid Working
• Competitive Package
• Supportive Culture

About the company

QuantumLoopAI is the UK’s market-leading provider of AI-powered telephony, voice agent and chatbot solutions for primary care. Our flagship product, EMMA, streamlines patient communications, slashes call-handling costs by up to 80%, and aligns seamlessly with NHS systems and regulations.