At a Glance
- Tasks: Design and optimise AI models for our innovative healthcare chatbot and voice agent.
- Company: Join QuantumLoopAI, transforming patient access to healthcare with cutting-edge technology.
- Benefits: Competitive salary, potential share options, and professional development opportunities.
- Other info: Flexible start date and commitment to diversity and inclusion.
- Why this job: Make a real impact on patient outcomes while working remotely with a supportive team.
- Qualifications: Experience in prompt engineering, LLMs, and strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
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.
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.
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
- 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.
CONTACT
We would love to hear from you. Questions about this role? Contact careers@quantumloopai.com
AI/ML & Prompt Engineer LLM, RAG & Voice Agent in London employer: QuantumLoopAi
QuantumLoopAI is an exceptional employer, offering a unique opportunity for qualified NHS GPs to transition into a commercial role while leveraging their clinical expertise. With a strong focus on employee growth, the company provides comprehensive B2B sales training and direct mentorship from senior leaders, ensuring that your career progression is based on merit. Located in the vibrant Canary Wharf area, employees benefit from excellent transport links and a supportive work culture that values innovation and collaboration in improving patient access through technology.
StudySmarter Expert Advice🤫
We think this is how you could land AI/ML & Prompt Engineer LLM, RAG & Voice Agent in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like QuantumLoopAi!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI/ML & Prompt Engineer LLM, RAG & Voice Agent at QuantumLoopAi.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like QuantumLoopAi.
✨Apply Directly through Our Website
When you find a suitable opening like AI/ML & Prompt Engineer LLM, RAG & Voice Agent at QuantumLoopAi, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AI/ML & Prompt Engineer LLM, RAG & Voice Agent in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at QuantumLoopAi, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at QuantumLoopAi. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at QuantumLoopAi
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at QuantumLoopAi!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.