Softvér, Umelá inteligencia / Machine Learning, Zdravie

Paris, Berlin, Cambridge

Organization and methodologies

Methodolgy & Delivery

  • Agile: 2 weeks sprint development + 1 week testing/validation
  • Xtrem programing: peer programing on demand
  • 1 production release / 3 weeks

Tech Company Mindset:

  • shared roadmap between « Tech » & « Product) (50/50)


  • Roadmap planning every quarter
  • Sprint planning every 2 weeks

Mentoring / Inspiration

  • Tech workshop 1h/week, with presentation and discussion
  • Training on specific challenging topics

Organization: 4 autonomous squads (Devs, QAs, Products)

Equipment: Linux and Mac friendly

And last but not least… weekly afterwork 😁

Projects and tech challenges

💪🏻 Patient Mobile Solution (PMS)

💪🏻 Patient Mobile Solution (PMS)

The Patient Mobile Solution, called PMS, is a simple single web-page app on a mobile phone that helps the patient to justify connectivity issues with their pacemakers and reports their symptoms during therapeutical guidance.

What has been a meaningful success for our teams in this project, was to be able to deliver a product, from scratch, involving 3 different teams, each of them working on an isolated set of microservices with curated technical specifications in a matter of weeks.

We have been able to benefit from the flexibility of our microservice by using our event-driven architecture, integrated API documentation, and highly qualitative specification process.

Today this project helps thousands of patient in their daily care.

💪🏻 Data Pipeline Agent (DPA)

The DPA is one of the most critical aspect of our solution.

Being able to ingest data from manufacturers in a fast, scalable and secure way is quite complex. At the beginning of Implicity, we could not imagine how much and how hard it would be to process that quantity of information.

Designing the right system to absorb a large amount of data, on a daily basis, with security and traceability constraints is one of the most challenging parts of our technical stacks.

Our ingestion teams had a challenging couple of years to continue assuming the liveness state of the ingestion pipeline and rethink all the design to ensure that we will maintain this quality of service with 10 to 100 times more data.

Today, thanks to the hard work of a passionate team of engineers, we are now closer to the goal of having a complete Ingestion pipeline that is no longer limited by its design to ingest an illimited quantity of data on a daily basis.

💪🏻 Data Pipeline Agent (DPA)

Recruitment process

  • 1st step: 15-20min « HR call screen », just to check that it is a mutual good idea to move on in a process
  • 2nd step: 1h « Manager interview » with the CTO (generalist interview: hard skills, soft skills, cultural fit, etc.)
  • 3rd step: 1h15 « Tech interview » with 2 members of the team (just oral questions on your hard skills)
  • 4th step: 45min « Final interview », with anyone that would like to come for last questions (often HR & CTO, for soft skills questions)

The whole process usually lasts 10 days & offer usually follows within 24h after last interview 🤞🏻