Backend Engineer - AI Infrastructure
About The Position
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.
Requirements
- Solid backend 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
Nice To Haves
- Familiarity with pipeline tooling (Airflow/Dagster/Prefect), queues (Kafka/SQS/PubSub), and common data formats (Parquet/JSON)
- Comfort with cloud infrastructure (AWS/GCP/Azure), containers, CI/CD, and basic DevOps hygiene
- Experience with LLM support systems (vector DBs, embeddings, RAG patterns, eval frameworks) and/or distributed compute (Spark/Ray)
Responsibilities
- 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
Benefits
- Arbol is proud to offer its full-time employees competitive compensation and equity in a high-growth startup.
- Our health benefits include comprehensive health, dental, and vision coverage, and an optional flexible spending account (FSA) to support your health.
- We offer a 401(k) match to support your future, and flexible PTO for you to relax and recharge.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
