Jerry.ai is looking to scale from 5M to 50M users by building automation systems that allow users to self-serve, stay insured, and have a seamless car ownership experience, thereby automating complex business processes and shaping the future of insurance tech.
Requirements
- At least 2 years full stack engineering experience building production-grade software, ideally prior experience building large scale distributed systems for a fast-growing consumer-facing software.
- Strong foundations in data structures, algorithms, and systems design matter more than having previous experience with specific languages or frameworks.
- TypeScript, Nest.js, Next.js, React, React Native, Expo
- GraphQL
- Postgres, DynamoDB, Clickhouse, Redis
- AWS, microservices, containerized services on ECS/EKS, asynchronous processing on Lambda
Responsibilities
- Build automation systems that handle complex insurance servicing tasks end-to-end (policy endorsements, cancellations, document uploads, reinstatements) or reduce policy cancellations, improve renewals, and ensure users always have the best coverage.
- Compose backend business logic that drives automation while respecting complex insurance carrier rules.
- Design backend pipelines that sync customer policy data, deliver timely alerts, and power seamless re-shopping experiences.
- Optimize and scale our internal tools (think: in-house DocuSign for servicing) to reduce agent intervention to nearly zero.
- Collaborate closely with product, data, and engineering ops to anticipate churn and improve customer retention.
- Continuously improve our backend systems, APIs, and microservice architecture.
- Explore new technologies, like AI/LLM tools.
Other
- Work on software that directly impacts millions of users
- Automate complex business processes
- Work on projects that excite you.
- Work asynchronously across time zones, with minimal meetings but strong collaboration through Asana and Slack.
- Comfortable working asynchronously across teams and time zones, with excellent communication skills.
