I'm a logical problem solver, advocate for simple solutions. Overall a generalist and quick thinker, I provide ideas taking into consideration the bigger picture and business needs, and I pride myself on being able to develop and implement simple systems quickly and efficiently.
Built a range of insurance products with FastAPI and React to convert unorganized documents, into structured data, using Computer Vision and Entity Recognition patterns (rekognition, textextract, narwhal) along with human input and validation. Also developed tools and internal dashboards to provide metrics to the operations team, resulting in increased productivity and cost savings. Led the team in adding code conventions and documentation whilst delivering results on both the backend and frontend.
Working in the Product team as a fullstack engineer, expanding the exisiting service oriented codebase with new features and mantaining the Heroku/AWS Hybrid architecture. I migrated the existing claim backend from using Django forms to a REST API architecure to be used by thousands of users every day. Led the development of integrations with external financial and insurance partners (TDS, Munich Re, Reapit, Openbanking) and planned technical roadmaps and tasks for fellow engineers. Assisted in hiring and onboarding and mentoring junior and senior engineers.
As part of the Client Success team, I built features for the Enterprise side of the business, The tech stack was primarily custom PHP with frequent use of Angular, SQL, and Bash. Successfully led A/B tests which resulted in raising user retention by 10%. Our team was also part of the migration of the website from Jquery and AngularJS to Angular 2+. Occasionally assisted the API team to fix bugs in Python. Assisted in hiring and onboarding and mentoring junior engineers.
Led the backend development of the initial MVP of the product: a platform for health assestement and B2B improvement programs. I introduced logging, documentation, unit testing, and 2fa to the existing codebase. I also upgraded the legacy Django version to a supported one. Setup infrastructure for health data retrieval to be used on future machine learning scenarios using Scikit-learn to enable predictability on possible user conditions.
Initially assigned with the development of the infrastructure of the main Django app which communicated without remote devices. I used MQTT as a pub/sub broker, sending a Protobuf-encoded message every 5 seconds for real-time client interaction and visualization of their electrical consumption. Test Driven Development was used throughout the project. Towards the end of the role, I implemented continuous integration with Jenkins for our backend and maintained the embedded Linux distro (Yocto) of the remote devices.