About the job
About Cartesia
At Cartesia, our vision is to create the future of AI—an intelligent, interactive system that seamlessly integrates into your daily life. Today, even the most advanced models struggle to process and analyze vast streams of audio, video, and text data—1 billion text tokens, 10 billion audio tokens, and 1 trillion video tokens—especially on-device.
We are at the forefront of developing the model architectures that will make these capabilities a reality. Our founding team, who met as PhD candidates at the Stanford AI Lab, pioneered State Space Models (SSMs), a novel approach for training efficient, large-scale foundational models. Our diverse team combines deep expertise in model innovation and systems engineering with a design-oriented product engineering team to create and deliver cutting-edge models and experiences.
With support from leading investors such as Index Ventures, Lightspeed Venture Partners, Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks, and others, along with guidance from an exceptional group of advisors and over 90 angel investors across various industries, we are well-positioned to redefine the AI landscape.
About the Role
We are seeking a passionate Product Software Engineer to join our team, focusing on building and scaling the platform infrastructure that supports Cartesia's voice AI products. In this role, you will develop composable platform components that enhance feature delivery across our API and conversational AI systems.
Your Impact
Develop and scale product platform components to facilitate Cartesia's growth.
Take ownership of critical product infrastructure end-to-end, including real-time systems.
Collaborate with product teams to identify common needs and create platform primitives that enhance their development speed.
What You Bring
A minimum of 3 years of experience as a backend or platform engineer with a focus on building scalable systems.
A customer-centric mindset that prioritizes outcomes over technical specifications.
A proactive approach to owning your work, tackling ambiguous challenges, and achieving results.
Strong decision-making skills regarding when to expedite development and when to invest in scalability.
Familiarity with our technology stack: TypeScript for frontend, Python and Go for backend. Expertise in all three is not required, but a willingness to learn is essential.
Nice-to-Haves
Experience with AI or machine learning systems.
Background in working with real-time data processing.

