Throughout my career I’ve had the privilege of working with a wide set of complex problems at the forefront of innovation, often in well known startups, but also in established institutions like the Norwegian sovereign wealth fund. I’ve consequently both learned and developed a strong research engineering skill set which I always seek to apply in creative ways, having tackled problems in the cloud native security realm, blockchain consensus protocols, systematic trading systems, confidential computing and ML infrastructure. Additionally, as a former Pervasive Parallelism CDT student at The University of Edinburgh School of Informatics and Edinburgh Performance Computer Centre (EPCC), I focused on formal modelling languages used to verify and simulate complex and adaptive, concurrent, and/or distributed systems (stochastic process algebras, invented by my supervisor). I also did a large amount of stochastic modeling prior to this as a researcher in risk modeling. Consequently I picked up an interest in using formalisms to synthesise real-world systems that are verifiable at design time. Furthermore, it made me appreciate the value of abstraction when tackling complex problems at large, and made me increasingly interested in AI as a consequence. At Oxford, I continued following this interest, albeit with a more applied focus, bringing my academic curiosity to a wide-set of problems related to software and systems security whilst pursuing extra-curricular research courses in AI safety and AI security accordingly.