Smplicare
Applied AI Software Engineering Intern
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Help us reimagine later life.
At Smplicare, we build simple, smart technology to help prevent falls in later life. We’re looking for an Applied AI Software Engineer to support the delivery of a key workstream within our funded project STEADI, an innovative research and development programme funded by Scottish Enterprise.
About the Project
Smplicare is developing a platform that helps older adults and carers understand and manage changes in frailty and fall risk. As part of this work, we are building an AI-assisted system for discovering reliable health information and converting approved sources into accessible content for our self-management mobile app.
The system will use large language models to search for relevant and approved health-information sources across a range of categories, summarise them for review, generate structured content drafts along with appropriate metadata and tags, and store outputs in our content management system.
You will help contribute to planning, and then take ownership of the defined technical project by prototyping and evaluating the system. You will work collaboratively with data, engineering, product, and clinical teams throughout. This is a hands-on software engineering project with significant opportunity to influence how the system is designed and delivered.
What You’ll Do
- Design and build an LLM-assisted pipeline for discovering relevant health-information sources on the web.
- Produce structured source summaries and information for human review.
- Build a pipeline that converts approved sources into app-content drafts.
- Generate proposed content metadata and tags using an agreed schema.
- Implement auditability across the pipeline.
- Contribute to the integration of approved drafts with production systems.
- Create evaluation systems for source quality and content accuracy.
- Investigate technical options independently, document decisions and communicate progress regularly
- Write maintainable code and clear technical documentation.
- Self-manage project backlog, communicate progress, and raise issues early.
- Collaborate with data, engineering, product, and clinical teams.
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What success looks like
By the end of the internship, we expect you to have delivered:
- A working prototype covering web discovery through to reviewed drafts
- A repeatable method for evaluating discovered sources and generated content.
- Tested and documented software that can form the basis of a production system.
- Documentation around ideas, decisions, implementation approaches, limitations, and risks.
Who we’re looking for:
We are looking for someone who:
- Is studying towards, or has recently completed, a degree in computer science, software engineering, health informatics, data science or any related subject / experience.
- Can build software in Python.
- Understands core software engineering practices such as version control and code reviews.
- Can break an ambiguous problem into manageable pieces and work with a high degree of independence.
- Communicates technical decisions, progress, and blockers clearly.
- Is interested in responsible AI and digital health.
- Approaches health information carefully.
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Desirable skills
- Experience using LLM APIs or building LLM-based applications.
- Experience with search, retrieval, embeddings, or RAG.
- Experience with AWS or another cloud platform.
- Experience with data pipelines and relational databases.
- Health informatics or clinical knowledge.
What we offer
- Flexible hybrid work model (2–5 days/week in our Glasgow office, with remote flexibility)
- 23 days paid leave (15 days holiday + 8 bank holidays)
- The chance to make your mark on a startup at a key stage of growth and contribute directly to its success
- The possibility of growing into a permanent role as Smplicare expands. This cannot be guaranteed, but our aim is to prove the long-term value of the role—not simply fill a 9-month post.
- A small, values-led team where your voice matters and your work has visible, real-world impact
- The chance to make a real difference in helping older adults live stronger, more independent lives
Type: Full-time (35 hrs/week), fixed term (9 months) with the potential to become permanent
Project Salary: £20,000 - 25,000 (9 months) (£25,000-£30,000 annual salary)
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