Backend Engineer

at  Cytora

We are a high-growth Series-B InsurTech start-up using data and machine learning to revolutionize the insurance industry. You will be joining a strong and mission driven team, working to build a customer facing product that fundamentally changes the way insurers evaluate risk, enabling them to move from highly manual workflows to digital risk flows. Cytora’s Risk Stream is a serverless and cloud native SaaS platform that automates the digitisation, evaluation and decisioning of risks for commercial insurers. Our product drastically improves the working lives of our users, enables our customers to cover more risks, more competitively.

BELOW YOU CAN FIND THE REQUIRED AND PREFERRED QUALIFICATIONS.

We made this list quite extensive so that you also get a taste of our tech stack!

THE ROLE

As backend engineer at Cytora, you will be joining a backend functional team. As such, the teams are small (maximum 4/5 people) and work independently of each other.
Each team has a technical lead and a product owner steering the team to make sure we deliver the right features. Regardless of team you join, you will be prototyping, implementing, shipping and supporting features that are changing the insurance industry.
The core of our product is to digitize risks and to accomplish that we rely heavily on Generative AI. Our engineering and product teams are distributed across Europe.

THIS ROLE REQUIRES EXPERIENCE WITH:

• Git (we use GitHub)
• Python (buzzwords: msgspec, httpx, pydantic, fastapi, structlog, sqlalchemy, alembic, jinja2, pytest, ruff, mypy)
• Mypy (we use mypy, a lot. We also welcome candidates with experience with other static type checkers!)
• Rest APIs
• Relational Databases (we use Postgres)
• Docker (we use Docker to package our code, and docker-compose to run it locally)
• AWS, and more specifically with:

THIS ROLE BENEFITS FROM EXPERIENCE WITH:

• Redis
• GCP, and more specifically with:
• GCP BigQuery (we use it to power our analytics)
• OCR engines (we use AWS Textract, GDocAI, and we have used tesseractOCR in the past)
• Prompt Engineering
• Weaviate (we use it for RAG in LLM powered tasks and for hybrid searches)
• Kubernetes (we run Weaviate and other specific services* on Kubernetes)
• CircleCI
• DataDog
• Auth0 (we use it, but we would rather not have to :face_exhaling:)
• Role Based Access Control
• JsonSchema
• Pusher (we use it to push notifications to our Frontend Web App)
• LocalStack (we use it to mock AWS services locally)
• Terraform