• Collaborate effectively across engineering, product, and design disciplines to shape solutions and deliver outcomes • Pragmatic approach to evolving technology and modernising applications incrementally. • Mentor engineers and contribute to a strong quality culture through reviews, testing, and technical guidance • Ability to influence technical direction through engineering standards, design discussions, and technical leadership • Track record of technical leadership without a management title: setting standards, unblocking others, making architectural calls in ambiguous situations.

• Designing and building scalable backend services in Go, working with PostgreSQL and DynamoDB • Implementing event-driven architectures with RabbitMQ and owning production systems end-to-end • Building exceptional user experiences across mobile app (Angular/Ionic) and web app (React) • Owning the full implementation of features from database schema design and API development to implementing UI changes • Bringing new patterns and tools to the team across both frontend and backend

• Architect, implement, and maintain decision science libraries that will be used in KoBold’s mineral exploration analyses. • Build tooling to increase the velocity of our decision making, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable pipelines; and organizing ML models and their outputs for repeatability and discoverability. • Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code • Collaborate with data scientists, geoscientists and engineers to invent the modern decision science technology for mineral exploration • Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery. Travel is approximately twice per year depending on project needs.

• Architect, implement, and maintain foundational scientific computing libraries that will be used in KoBold’s mineral exploration analyses. • Build tooling to increase the velocity of our machine learning progress, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable ML pipelines; and organizing models and their outputs for repeatability and discoverability. • In collaboration with data scientists, build models to make statistically valid predictions about the locations of economic concentrations of ore metals within the Earth’s crust. • Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code • Collaborate with data scientists, geoscientists and engineers to invent the modern scientific computing stack for mineral exploration • Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery. Travel is approximately twice per year depending on project needs.