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For Companies At a Glance
- Tasks: Shape the future of clinical AI by owning backend and ML infrastructure.
- Company: Exciting med tech spinout from Imperial College London with a mission to improve healthcare.
- Benefits: Competitive salary, 25 days leave, flexible hybrid work, and access to clinical networks.
- Other info: Clear path to Head of Engineering as we scale and innovate.
- Why this job: Make a real impact in healthcare while advancing your career in a high-ownership team.
- Qualifications: 5+ years in software engineering with strong Python skills and experience in Azure or AWS.
The predicted salary is between 70000 - 90000 £ per year.
The Opportunity
We are an Imperial College London med tech spinout building AI-powered clinical decision-support tools certified as Software as a Medical Device (SaMD). Our platform uses real-world EHR data to identify patients at risk of preventable harm — giving NHS clinicians time to act. We are a small, high-ownership team operating at the intersection of clinical AI and healthcare infrastructure. This is a foundational engineering hire with a clear path to Head of Engineering as we scale.
The Role
You will own and shape the technical core of a live clinical AI platform — working across backend services, ML infrastructure, and hospital data integrations. You will have a direct line to the CTO and CEO from day one, with real influence over architectural decisions on a system processing real patient data across NHS trusts.
What You'll Do
- Own and extend the backend and ML infrastructure of a production SaMD system
- Design and implement integrations with hospital systems (EHR, HL7/FHIR), including partnerships with major healthcare data platforms
- Build and maintain Python/Azure-based services — APIs, data pipelines, monitoring and audit frameworks
- Write software that meets medical device quality standards, producing artefacts that support regulatory submissions
- Collaborate with clinical, data science, and regulatory stakeholders
- Help define engineering culture and processes as the team grows around you
What We're Looking For
- 5+ years of professional software engineering experience with a strong Python background
- Proven experience building and operating production services on Azure or AWS
- Comfort with data-heavy systems — pipelines, databases, REST APIs — and a taste for clean architecture
- Strong written communication; able to document work to regulatory audit standard
Nice to Have
- Experience in a regulated software environment (medical devices, fintech, defence, or similar)
- Familiarity with FHIR/HL7 or clinical EHR systems
- Exposure to ML model deployment or monitoring in production
Tech Stack
Python · Azure · Terraform · Docker · ML Pipelines · FHIR / HL7 · GitHub Actions
What's on Offer
- Competitive renumeration package, depending on experience
- 25 days annual leave + bank holidays
- Access to clinical and academic networks
- Flexible hybrid working, London base
Growth Path
As we move through our next funding round and scale clinical deployments, the expectation is that you grow into Head of Engineering or equivalent — owning technical strategy, building a team, and sitting at the table for product, regulatory, and commercial decisions.
Senior Software Engineer – Clinical AI employer: Prelego
Contact Detail:
Prelego Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Software Engineer – Clinical AI
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those connected to clinical AI or healthcare tech. Attend meetups, webinars, or even just grab a coffee with someone who works at a company you're interested in. Personal connections can often lead to job opportunities that aren't advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to Python, Azure, or ML. If you’ve worked on any healthcare-related projects, make sure to highlight them. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your experience with backend services and data-heavy systems. Also, think about how you can contribute to defining engineering culture as the team grows — they’ll want to see your vision!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in being part of our team and contributing to the exciting work we’re doing in clinical AI.
We think you need these skills to ace Senior Software Engineer – Clinical AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match our job description. Highlight your Python expertise and any experience with Azure or AWS, as these are key for us.
Showcase Your Projects: Include specific examples of projects you've worked on, especially those involving clinical AI or regulated environments. We love seeing how you've tackled real-world problems!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate strong written communication, so make sure your points are clear and easy to understand.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team.
How to prepare for a job interview at Prelego
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and Azure. Brush up on your experience with data-heavy systems and be ready to discuss how you've built and maintained production services in the past.
✨Understand Clinical AI
Familiarise yourself with clinical decision-support tools and the importance of EHR data in healthcare. Being able to speak knowledgeably about how your work can impact patient care will show your passion for the role and the industry.
✨Prepare for Architectural Discussions
Since you'll have a direct line to the CTO and CEO, be prepared to discuss architectural decisions. Think about clean architecture principles and how they apply to scalable systems, and be ready to share examples from your previous work.
✨Showcase Your Communication Skills
Strong written communication is key, especially when it comes to documenting work for regulatory standards. Bring examples of documentation you've created in the past, and be ready to explain how you ensure clarity and compliance in your work.