Founding Engineer, Backend + Infra

Clarity•San Francisco, CA

About The Position

Clarity is an operating system for revenue in a business. An AI-powered workspace that sales, customer support, and product work out of to close customers, prevent churn, and build product. We are passionate about building high-quality software and products that people love. We have growth mindsets and are excited about pushing ourselves to be the best we can be. We think we’re onto something big, and are doing everything we can to make it happen. The vision for Clarity is made possible by the advent of large language models and generative AI. Our product ingests massive amount of data that needs to be ingested from tools across the stack, reliably processed and analyzed into our intelligence, and then served to the user instantly. Our customers rely on Clarity to build their businesses and need it to work reliably and correctly every single day and we’re hiring a Founding AI engineer to help lead these backend efforts. We’re a small team that moves quickly while keeping a high quality bar. We’re looking for someone who is excited about taking ownership of large parts of Clarity’s product and AI stack. We’re looking for someone who is passionate, optimistic, and has a deep-rooted desire to build something great (and to have fun while doing it).

Requirements

Founding AI engineer to help lead these backend efforts
Excited about taking ownership of large parts of Clarity’s product and AI stack
Passionate, optimistic, and has a deep-rooted desire to build something great

Responsibilities

Architect and own our data processing pipeline end-to-end
Create maintainable abstractions to enable the engineering team to build reliably
Define the data ontology across countless integrations that Clarity supports
Set the culture for quality and efficacy for the engineering team
Own the deployment process, ensuring consistent and stable releases
Scale Clarity’s infrastructure as we scale to ensure uptime
Own observability and monitoring for the stack
Set team processes around on-call and incident responses
Ensure we can trace issues and debug effectively with strong monitoring and observability
Establish an evaluation framework to ensure response quality as we make changes
Optimize foundation model costs without compromising on response quality
Build frameworks to make our AI systems modular and extensible
Ability to build product experiences end-to-end
Proactively addressing bugs and fixing paper cuts
Jump in to support customers when they run into issues or have requests