Location: Preference for San Francisco, Hybrid; open to remote candidates

Reports to: CTO, Co-founder

About Coverbase

The foundation of the modern global economy is built on a dense network of counterparty trust and risk. In the past 50 years, companies have evolved from relying on a couple of wholesalers and vendors, to utilizing 100+ SaaS vendors, contract partners, and cloud providers. Since each counterparty has their own idiosyncratic internal processes and risk profiles, businesses end up spending millions of dollars and countless man-hours conducting due diligence.

Coverbase's mission is to streamline this business-to-business assessment, reducing human toil, and allowing organizations to work together safely and reliably. We employ modern AI techniques to organize vast amounts of unstructured data and compare them against policies to identify key risks to the business. We have customers across Fortune 500 companies in insurance, higher education and finance, including five of the top 25 banks in the US.

Clarence, our CEO, was previously the cofounder and CTO of Unit21, a Series C fraud detection tooling company that has raised approximately $100 million to date. Kao, our CTO, led the engineering team at Stripe that helped start the Banking-as-a-Service product. We’ve raised $19.5M from world-class investors and our team of 12 have built important products at Google, Mapbox and Waymo.

Expectations

We're seeking an AI engineer to develop AI features that are the bread-and-butter of AI-native product. We are looking for impact-driven individuals who take pride in shipping delightful products and are not merely focused on the intellectual interestingness of the work. We're also looking for folks who care not just about their work, but the people around them - we're building a team that's as kind as they are talented.

Responsibilities

Some subset of the following:

• Build LLM features that are the bread-and-butter of our AI-driven product, from ideation to productionalisation with scaling.
• Develop benchmark to evaluate our LLM performance and combat LLM hallucination.
• Take ownership of the full development lifecycle, including infrastructure and front end work surrounding the AI features.
• Foster a constructive environment for code reviews, mentoring, and knowledge sharing.

Requirements

• You have experience with developing LLM applications.
• You have experience with rigorous, quantitative work, such as PhD-level research, machine-learning modeling or data science projects.
• You're able to thrive in a dynamic, early-stage startup environment. While this is an AI-focused role, AI development is not 100% of the role. We expect versatility, though not necessarily domain expertise, in other parts of the stack, and that you can jump in to ship a product end-to-end.
• You have high standard for code quality.

Why join us?