Cartesia

Tech / AI / Software

EnterpriseEngineer

₹70–90L san francisco, california, united states; london, england, united kingdom; Bangalore, Karnataka, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Enterprise Engineer at Cartesia. Skills: backend engineering fundamentals, infrastructure, platform services, core abstractions, Go, Python. Architect and build enterprise-grade systems such as On Prem Deployments & Agent Infrastructure. Own the design and delivery of durable, first-class platform capabilities shaped by enterprise needs — the abstractions, core changes, and infrastructure that Cartesia's largest customers build on top of”

What You'll Achieve.

advance our mission of building real-time multimodal intelligence by delivering agentic voice AI solutions directly into production for our customers; scale across the most demanding enterprise environments globally

Industry & Context.

Tech / AI / Software
Eligibility Requirements

Visa sponsorship support

What They're Looking For.

Must Have

backend engineering fundamentals, designed and shipped infrastructure, platform services, or core abstractions that other teams build on top of, Go and/or Python, long-term maintainability and modularity, collaborating cross-functionally, translating customer feedback into actionable product and platform improvements

Nice to Have

enterprise-grade concerns: deployment in customer-managed infrastructure (VPCs, on-prem), compliance regimes, observability, multi-tenancy, and security hardening

What You'll Do.

Architect and build enterprise-grade systems such as On Prem Deployments & Agent Infrastructure

Own the design and delivery of durable

first-class platform capabilities shaped by enterprise needs — the abstractions

and infrastructure that Cartesia's largest customers build on top of

Turn recurring patterns from customer deployments (gaps

eval results) from one-off workarounds into scalable

long-term platform primitives

Define and raise the bar for reliability

and operational maturity across Cartesia's enterprise surface area

How You'll Work.

Team & Collaboration

collaborating cross-functionally

Full Job Description

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 We’re hiring an Enterprise Engineer to advance our mission of building real-time multimodal intelligence by delivering agentic voice AI solutions directly into production for our customers. YOUR IMPACT - Architect and build enterprise-grade systems such as On Prem Deployments & Agent Infrastructure - Own the design and delivery of durable, first-class platform capabilities shaped by enterprise needs — the abstractions, core changes, and infrastructure that Cartesia's largest customers build on top of - Turn recurring patterns from customer deployments (gaps, incident themes, eval results) from one-off workarounds into scalable, long-term platform primitives - Define and raise the bar for reliability, security, and operational maturity across Cartesia's enterprise surface area - You'll have significant ownership over the core capabilities that determine whether Cartesia can scale across the most demanding enterprise environments globally WHAT YOU BRING - Strong backend engineering fundamentals — you've designed and shipped infrastructure, platform services, or core abstractions that other teams build on top of

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