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Cartesia

Develops foundation models with subquadratic architectures

Enterprise Engineer

Backend EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Strong backend engineering fundamentals, including designing and shipping infrastructure, platform services, or core abstractions used by other teams.
  • Proficiency in Go and/or Python.
  • Ability to think in terms of long-term maintainability and modularity.
  • Ability to collaborate cross-functionally and translate customer feedback into actionable product and platform improvements.

Responsibilities

  • Architect and build enterprise-grade systems, such as on-premises deployments and agent infrastructure.
  • Own the design and delivery of durable, first-class platform capabilities shaped by enterprise needs, including abstractions, core changes, and infrastructure that the largest customers build on.
  • Turn recurring patterns from customer deployments, including gaps, incident themes, and evaluation results, from one-off workarounds into scalable, long-term platform primitives.
  • Define and raise the bar for reliability, security, and operational maturity across the enterprise surface area.

Desired Qualifications

  • Experience with enterprise-grade concerns, including deployment in customer-managed infrastructure such as virtual private clouds and on-premises environments, compliance regimes, observability, multi-tenancy, and security hardening.

About the Company

Cartesia

Develops foundation models with subquadratic architectures

Cartesia.ai develops advanced AI foundation models using new subquadratic architectures and state space models. Its models are designed as underlying systems that can be adapted for many applications and are released in part under open-source licenses (e.g., Apache 2.0), with licensing, partnerships, and consulting as revenue streams. The company’s products work by providing large, adaptable AI models that clients can license or customize for specific needs, enabling faster processing and efficient inference compared to traditional designs. Cartesia differentiates itself from competitors by using subquadratic, state space approaches instead of relying mainly on standard Transformer models, and by combining open-source releases with enterprise partnerships. The goal is to help businesses and research institutions access powerful, adaptable AI capabilities while building a community around its technology and sustaining revenue through licensing and services.

Company size
51-200
Company stage
Late Stage VC
Total funding
$191M
Headquarters
San Francisco, CA
Founded
2023

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