About the job
About Cartesia
At Cartesia, our vision is to develop the next wave of artificial intelligence: a seamless, interactive intelligence that is accessible anytime and anywhere. Even the most advanced models today struggle to consistently analyze extensive streams of audio, video, and text—this includes a staggering 1 billion text tokens, 10 billion audio tokens, and 1 trillion video tokens—much less accomplishing this directly on devices.
We are at the forefront of designing the model architectures that will revolutionize this capability. Our founding team, who met as PhD students at the Stanford AI Lab, pioneered State Space Models (SSMs), a groundbreaking tool for training efficient, large-scale foundational models. Our diverse team blends in-depth knowledge of model innovation with strong systems engineering and a product-driven engineering approach to create and deploy cutting-edge models and experiences.
We are backed by prestigious investors including Index Ventures and Lightspeed Venture Partners, along with contributions from Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks, and many others. We are privileged to have the mentorship of numerous esteemed advisors and over 90 angel investors from various fields, including leading experts in AI.
About the Role
We are seeking an AI-native Software Engineer focused on Developer Acceleration to enhance the developer experience and optimize the speed at which Cartesia engineers can ship solutions. This role involves creating innovative tooling at the cutting edge of AI programming, and developing a comprehensive playbook that empowers both engineers and non-engineers to efficiently deploy consistent and maintainable internal tools independently.
Your Impact
Design workflows that facilitate Cartesia's transition from problem identification to solution implementation with minimal human oversight.
Remain informed about the latest advancements in AI-assisted development and champion its adoption within Cartesia.
Develop automated end-to-end development and evaluation frameworks that empower coding agents to refine solutions and self-correct.
Create a playbook for the Cartesia team to build data-connected, IAM-aware internal tools for both human-in-the-loop and automated processes.

