Cartesia

Software Engineer, Product

*HQ - San Francisco, CA

Sponsorship not specifiedDetected 170 days ago

TypeScriptPythonPostgreSQLRedisDatabricksPrometheusDatadogPlatform EngineeringSystems Engineering

About the role

You'll code composable platform components that accelerate feature delivery across our API and conversational AI systems.

Build and scale product platform components to support Cartesia's growth.
Own critical product infrastructure end-to-end, such as realtime infra.
Work alongside product teams to identify shared needs and build platform primitives that multiply their velocity.
Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.
We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others.
We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.
🦖 Your own personal Yoshi

3+ years of experience as a backend or platform engineer building scalable systems.
Comfort across our stack: TypeScript on the frontend, Python + Go on the backend.
You think in terms of customer outcomes, not just technical requirements.
Enjoy full ownership of your work, and effectively navigate ambiguous problems to deliver results.
Strong judgment on when to move fast and when to invest in scalability.
Comfort across our stack: TypeScript on the frontend, Python + Go on the backend. You don't need to be an expert in all three, but you're not afraid of any of them.
Background in observability infrastructure (Datadog, Prometheus, OpenTelemetry) and building internal tooling for debugging production systems.
Note: Cartesia participates in E-Verify and will provide the federal government with Form I-9 information to confirm employment eligibility after hire.
🏢 In-office policy: We're an in-person team based out of offices in 🇺🇸 San Francisco, 🇬🇧 London and 🇮🇳 Bangalore. We love being in the office, hanging out together, and learning from each other every day.
🌎 Visa sponsorship: We provide visa sponsorship support and assess each circumstance on a case-by-case basis. However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can't always guarantee success. Your Recruiter will work with you to understand your visa sponsorship needs from the first call.

Each of these is a plus, but not required to qualify for the role.
Experience with PostgreSQL, Redis, NATS, or similar data and messaging systems at scale.
Familiarity with real-time streaming systems, or WebRTC.

💰 Compensation Competitive base salary alongside attractive equity package.
🩺 Health Insurance Fully covered medical insurance along with dental and vision for you and your family.
🧑‍🧑‍🧒‍🧒 Parental Leave 9 weeks paternity & 12 weeks maternity leave
🚆 Commuter Allowance A monthly stipend to help you get to and from the office.
🏖️ Flexible PTO Take as much time as you need to recharge your batteries.
We consider qualified applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other legally protected status.

Our mission is to architect AI that learns from and interacts with the world like humans do.
Cartesia is hiring a Software Engineer, Product to build and scale the platform infrastructure that powers Cartesia's voice AI products.

We provide visa sponsorship support and assess each circumstance on a case-by-case basis.
However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can't always guarantee success.
Your Recruiter will work with you to understand your visa sponsorship needs from the first call.

This listing is sourced directly from Cartesia's careers page and normalized into a canonical job model.