We are looking for a junior plus-level Fullstack Developer to support the development of our products. We mainly focus on two projects:
As we prepare for critical audits and market entry, you will balance maintaining a mature codebase with the rapid development of new, high-performance features. This isn't just about writing code; it’s about developing a certified medical device that will change patient outcomes. You’ll be working with Web APIs, LLMs, and automated testing to ensure our medical assistant remains robust, compliant, and ready for global scale.
Ability to work independently with an even split between backend (Python) and frontend tasks (Vue/Nuxt)
Experience with modern, typed, and asynchronous Python used in web development
Experience with frontend technologies (we use Vue.js and Nuxt.js)
Being comfortable with fast-paced environments
Ability to follow established Architectural or Design Patterns
Practical knowledge of relational databases (we use PostgreSQL)
Familiarity with automated testing (Pytest + Playwright) and static code analysis (Pylint, Mypy)
Comfortable using English and Polish for both written and spoken communication
Developing an API-first platform and a medical agent, specifically tackling the challenges of multitenancy and the integration of text/voice LLM technologies
Contributing within technical lifecycle of our Medical Device features (from effort estimation and risk assessment to ensuring all development meets the rigorous documentation standards required for medical audits)
Supporting the product development as a full-stack developer with an even split between backend (Python) and frontend (Vue/Nuxt)
Supporting the team’s efforts in maintaining a robust CI/CD pipeline and automated testing, ensuring the balance between rapid feature growth and mature system maintenance
Supporting other teams with technical knowledge, especially Tech Support or Customer Success
Working with agentic tools like Cursor or Claude Code
Working in an environment where automated testing, code reviews, and technical documentation are part of the daily definition of 'done’
Familiarity with concepts related to LLMs (RAGs, vector databases, prompt engineering, and performing evaluations of model outputs)
Familiarity with CI/CD and DevOps concepts or tools like Docker, Docker Compose, CI/CD pipelines (we are using GitLab CI), Kubernetes