Oslo, Oslo, Norway
- Architected and led the migration of the authorization & authentication system to a new provider, allowing resource sharing & fine-grained access control across all Findable products. - Designed and implemented a highly-scalable & fault-tolerant integration with Microsoft SharePoint for data ingestion and export which enabled several pilots with enterprise customers. - Implemented event-tracking & observability for a file-processing pipeline delivering real-time progress updates to customers while also enabling analysis & recovery in case of failures. - Joined an at-risk project, ensuring the timely delivery of a functional product by aligning on core requirements, revising scope and contributing to the implementa- tion across the stack.
Joined in Mai 2022 as an intern and converted to full-time after 4 weeks. On leave for my Masters Thesis, returned in January 2024. - Contributed to the design, implementation and launch of an online-marketplace connecting over 100 manufacturers and contractors in the off-site construction industry. - Played a major role in architecting and executing the migration from a monolith to a serverless backend reducing load-induced outages to zero. - Migrated a data processing pipeline to AWS Step Functions to improve scalability, reduce outages, and reduce overall processing time by 70%. - Led the charge introducing new concepts and techniques to improve code quality, maintainability and readability (e.g. introducing unit tests, leveraging static typing, spreading awareness for good practices, etc.)
During my time at university, I was employed at several different chairs and projects: - Held/Tutored multiple introductory classes on Java for new and second year students. - Worked for the EveryAware Project (http://cs.everyaware.eu/) – a system for large-scale data storage and analytics. I was concerned with the Java+Spring-based backend of the application and mostly worked on migrating it from a relational database to a NoSQL solution. - Set-up of a small Kubernetes cluster which was then used to benchmark the behavior of Kubernetes auto-scaling mechanisms. - Worked on a framework for training and evaluating (neural) sequential recommendation systems. Examined the applicability of such systems to novel domains such as purchase data gathered from e-sports titles like Dota 2. In this context, we also developed a distributed crawler and processing pipeline for the large-scale collection of match replay files.
- Implemented role-based access control for a client’s internal employee portal. - Extended a power drill configuration tool to support newly released parts.