Software Engineer, Agent Harness
Position Summary & Responsibilities
About Cartesia
Our mission is to architect AI that learns from and interacts with the world like humans do.
We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. 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.
About the Role
Cartesia builds real-time multimodal intelligence: fast, state-of-the-art voice models, and the platform that puts them into production. We started as a research lab, pioneered the state space model architecture, and now we're bringing that research to customers through Managed Agents, our voice agents product.
In this role, you'll build the platform behind Managed Agents. Customers rely on our stack to run real-time, production-grade voice agents. You'll own the stack end-to-end and directly shape the latency, reliability, and developer experience of every agent built on Cartesia.
Your Impact
Evolve the realtime transport layer that carries audio between users and agents, expanding how customers connect across web, SDKs, and telephony without regressing latency or quality.
Trace and cut end-to-end conversational latency across the STT, LLM, and TTS pipeline.
Make agent deployments fast and resilient: faster cold starts, smarter scaling, graceful behavior under load.
Define how voice agent quality is measured, building eval suites, LLM-as-judge scoring, and regression tracking that catch quality and l
Key Role Competencies & Evaluation Highlights
Focuses on deep AI/ML engineering rigor, State Space Models (SSMs) comprehension, and low-latency systems optimization.
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