Forward Deployed Engineer

Arbol is a global climate risk coverage platform and FinTech company offering full-service solutions for any business looking to analyze and mitigate exposure to climate risk. Arbol’s products offer parametric coverage which pays out based on objective data triggers rather than subjective assessment of loss. Arbol’s key differentiator versus traditional InsurTech or climate analytics platforms is the complete ecosystem it has built to address climate risk. This ecosystem includes a massive climate data infrastructure, scalable product development, automated, instant pricing using an artificial intelligence underwriter, blockchain-powered operational efficiencies, and non-traditional risk capacity bringing capital from non-insurance sources. By combining all these factors, Arbol brings scale, transparency, and efficiency to parametric coverage.

What You'll Be Doing:

• Embed with internal teams and partners to scope messy, loosely defined problems and turn them into structured PRDs and working software

• Build and maintain internal tools, including pricing and decision engines, data apps, and AI-powered workflows

• Write the SQL and Python behind analyses, dashboards, and monitoring that leadership uses to make decisions

• Integrate third-party models, APIs, and data sources into our systems, and handle the mapping, transformation, and validation they need

• Prototype quickly in notebooks and scripts, then harden what works into reliable, tested production systems

What You'll Need:

• Experience working with the product lifestyle, from PRD creation to implementation

• Solid engineering skills in Python

• Strong understanding of data systems: SQL, schemas, indexing, partitioning, and performance tradeoffs

• Comfort with statistical concepts relevant to model evaluation, or experience interpreting metrics and distributions

What's Great to Have:

• Familiarity with pipeline tooling (Airflow/Dagster/Prefect), queues (Kafka/SQS/PubSub), and common data formats (Parquet/JSON)

• Familiarity with cloud infrastructure (AWS/GCP/Azure), containers, CI/CD, and basic DevOps hygiene