Senior Software Engineer - Mexico

Anzen is an insurtech startup founded by former insurance and tech executives who have collectively scaled three unicorns. We are working to completely disrupt the management insurance market. We are backed by leading investors including Andreessen Horowitz (a16z) and Madrona.
At Anzen, we are building the first insurance product of its kind. Every year, companies all over the United States file billions of dollars in insurance claims related to founder, management, and shareholder liability. We are using the latest advances in ML and NLP to understand risk better than ever before, and to provide companies with tools they can use to lower their risk.
We are expanding to Mexico, and are looking to hire a small team of talented Engineers who want to work alongside a team from an incredible set of universities (Cambridge, MIT, McGill) that have worked at some of Silicon Valley's most famous companies (Google, Oracle) and helped scale multiple companies into billion dollar organizations.
You will help build our core technology to ensure it can scale to hundreds of millions of dollars in insurance policies and use ML to help insurance underwriters be 5-10x more effective.

Responsibilities

• Work closely with Product, Design, and our Principal Engineer to take our vision through concept through rollout; building out an experience that customers love, and splitting that work into reasonable milestones.
• Architect and implement core pieces of our insurance infrastructure.
• Help hire amazing people and build the Engineering culture at Anzen.

Qualifications

• Strong academic background (Computer Engineering degree or equivalent)
• At least two years of experience building complex systems as part of a team.
• Familiarity with some components of the Anzen stack (TypeScript, React, Postgres, Redis, AWS)
• You are excited to take on completely new projects and also to provide fresh perspectives on existing implementations.
• Ideal candidates will have experience building software with strict quality and uptime requirements (e.g. financial systems)
• Ideal candidates will have experience or an interest in training or fine-tuning Machine Learning models.