Backend Engineer - AI Infrastructure

About this role

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.


Arbol is looking for a backend engineer to join the team to help build the data infrastructure for our production AI pipelines. In this role, you’ll own the full lifecycle of our production LLM applications: ingestion, transformation, storage, retrieval, evaluation, and monitoring. The ideal candidate has a strong quantitative background in math, statistics, or computer science. This is a hands-on role for an engineer that’s comfortable owning systems end-to-end and can move quickly without sacrificing quality.


What You'll Be Doing

• Build pipelines for structured and unstructured data including docs, PDFs, emails, and logs
• Design and implement backend services that support LLM workflows: retrieval, indexing, embeddings, batch processing, and job queues
• Own data quality end to end: validation, deduping, lineage, versioning, and reproducible runs
• Create observability for pipelines and LLM systems to surface issues quickly and identify root causes clearly

What You'll Need

• Solid backend engineering skills in Python
• Strong understanding of data systems: SQL, schemas, indexing, partitioning, and per...