Raincoat: Transformative Climate Insurance Technology Company

At Raincoat, we believe there's no easy answer to the climate challenge conundrum. Therefore, we are obsessed with solving this problem by building software products that positively impact and work for all world citizens. We partner with the world's most relevant insurance industry players to transform how people are protected from natural disasters. Governments and private companies have used our products to protect thousands of individuals and small farmers in Mexico, Colombia, Puerto Rico, and Jamaica.

The Role

You will be in direct contact with the science team, and your job will start where the science ends. The day-to-day tasks will require you to take a prototype of a mathematical/AI/etc. model and turn it into a production component. Whether it is a standalone microservice or a part of a larger ETL data pipeline, you will be responsible for the system to be running smoothly in the Kubernetes cluster or inhouse cluster computer. Because of the operational aspect, some former experience with Kubernetes is required. In this role, you will learn the science behind the models and engineering which goes into analysis of satellite datasets. It is expected that you will learn, through interaction with the scientists, the details of the algorithm and solve for unexpected failure modes. 

This role is an opportunity to join a rapidly growing company with a groundbreaking vision in a highly technical and scientific environment. This is a remote position so it's important that you navigate the organization with independence and a self motivated attitude.

Day to day

• Take over the code from the science team and turn it into production quality service. This often requires running the components on schedule (Dagster) or in a pub/sub environment.
• Build CLIs, REST/gRPC APIs
• Contribute and maintain python libraries
• Function as a “glue” engineer between the science team and SRE/DevOps
• Operate microservices, data pipelines and ensure operational reliability
• Optimize model execution to improve efficiency and solve for data pipeline failure modes
• Instrument the microservices/components with telemetry data and create alerts
• Create monitoring dashboards in Grafana to understand execution data pipeline and KPIs

What we value

• A curious generalist when it comes to software engineering: you enjoy learning new stuff
• Experience with GIS and remote sensing data (multi/hyper-spectral, radar/SAR, etc.) or Big Data
• (GeoSpatial) data wrangling tools/libraries: XArray, (Geo)Pandas, Numpy, GDAL
• A flare for visualizations: matplotlib, plotly, maplibre, deckgl, etc.
• Production level Python engineer (5 years), pytest, pyenv, poetry, and the rest of the python tooling
• Strong communication skills (written and oral) in English (C2 level). 

Bonus Points

• Msc in STEM: Science, Technology, Engineering, and Mathematics
• Dagster, Kubeflow for running AI models
• AWS, Kubernetes, Docker, monitoring (Grafana/Prometheus), OpenTelemetry
• gRPC/REST microservices design/operations
• Other programming languages (GO, C/C++)

What we offer

• 100% remote first company
• Stock Options plan
• Remote setup lump sum
• Health insurance benefit

Raincoat team members and founders come from a wide-range of backgrounds, perspectives and life experiences; this has created a culture of diversity, resilience and perseverance. We are committed to keeping these values but also include relevant culture elements of new team members joining to keep shaping Raincoats identity and solving the most fundamental climate issues.