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QuantumLoopAi

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

London
Posted 3 months ago
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About Quantumloopai

QuantumLoopAI is transforming how patients access healthcare. Our AI-powered reception system, EMMA, serves millions of patients, helping GP surgeries manage demand, reduce phone queues, and ensure patients get the right care at the right time. Backed by leading healthcare investors and working with stakeholders across England, we are building the future of primary care access. As we prepare for our Series A and expand our team, we are looking for exceptional people who want to make a genuine difference to healthcare.

About The Role

As our AI/ML & Prompt Engineer, you will own the intelligence behind EMMA — the LLM and RAG systems that power our chatbot, voice agent and telephony services. You will design, build and optimise the AI models and prompt architectures that allow EMMA to understand patient needs, retrieve accurate clinical information, and respond naturally across text and voice channels. This is a hands-on, high-impact role where your work will directly shape patient outcomes across hundreds of GP surgeries.

What You Will Do

Architect and deploy LLM- and RAG-based systems that ingest data sources, generate accurate responses, and power both 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 (Next.js, React) and backend (NestJS, Python) teams to integrate AI and voice agent components into our Azure-hosted microservices architecture Instrument AI and voice-agent pipelines, analyse logs and user feedback, troubleshoot edge cases, and implement continuous-learning improvements Stay abreast of the latest advances in LLMs, RAG, conversational AI frameworks, and (GDPR, DTAC) to inform our technical roadmap Define and execute rigorous test plans in collaboration 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

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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Requirements

ESSENTIAL

Demonstrable hands-on experience with prompt engineering, LLMs (e.g. GPT, LLaMA, Mistral), RAG frameworks, and voice-agent or dialogue-system design, with shipped projects or open-source contributions Advanced proficiency in Python for ML/AI development Experience building APIs in NestJS and familiarity with Next.js/React for frontend integration Strong understanding of Azure services (App Services, Functions, Cognitive Services), containerisation (Docker), and relational databases (MySQL) Experience designing microservices, distributed architectures and RESTful or GraphQL APIs Excellent written and verbal communication skills, with the ability to articulate complex AI and voice-agent concepts to technical and non-technical stakeholders Comfortable working remotely and collaborating asynchronously with a UK-based team during UK business hours (9:00 AM to 6:00 PM GMT/BST)

DESIRABLE

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

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LOGISTICS

Education: We value skills and experience over formal qualifications Working arrangements: Fully remote from India, aligned to UK business hours (9:00 AM to 6:00 PM GMT/BST) Start date: Flexible

Benefits

WHAT WE OFFER

Competitive package depending on experience Potential share options Professional development including conference attendance and CPD support Remote working with a collaborative, supportive team

How We Are Different

At QuantumLoopAI, you will join a team that is genuinely improving primary care. We move fast, take ownership, and celebrate wins together. Our culture values:

Impact over optics. We measure success by patient outcomes, not busy work Transparency. Open communication, honest feedback, shared context Ownership. You will have real autonomy to shape your work and our product Learning. We are building something new, and we learn from every experiment

DIVERSITY AND INCLUSION

We believe diverse teams build better products. We welcome applications from candidates of all backgrounds, and we are committed to creating an inclusive environment where everyone can do their best work. If you are excited about this role but do not meet every requirement, we would still love to hear from you.

RECRUITMENT SAFETY NOTICE

QuantumLoopAI will never ask candidates for payment or sensitive financial information during the recruitment process. All official communications come from @quantumloopai.com email addresses.

COME WORK WITH US

We would love to hear from you. Questions about this role? Contact careers@quantumloopai.com

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Skills

AI
ML
Prompt Engineering
LLMs
RAG
Voice Agent
Dialogue System Design
Python
NestJS
Next.js
React
Azure
Docker
Microservices
APIs
MLOps

Location

London, England, United Kingdom

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