Live opening · Posted 2 days ago
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About the role
Description supplied by the original job listing.
We're hiring a Forward-Deployed Engineer to advance our mission of building real-time multimodal intelligence by embedding directly with enterprise customers and delivering agentic voice AI solutions into their production environments. FDEs help customers succeed and grow by turning Cartesia's core product into deployed, high-impact solutions.
Responsibilities:
Write and ship production-grade code: Design, build, and deploy voice AI systems that power real enterprise workflows.
Own deployments end-to-end: Lead discovery, architecture, implementation, and rollout for strategic customer engagements.
Drive progress in ambiguity: Move projects forward when requirements are incomplete, constraints evolve, or systems fail in unexpected ways.
Deliver across complex infrastructure: Deploy across cloud, VPC, and on-prem environments while navigating security, networking, and compliance requirements.
Unblock critical integrations: Diagnose and resolve integration failures, performance bottlenecks, and deployment issues under real-world constraints.
Drive expansion through building: Identify new use cases and prototype solutions that deepen adoption and increase long-term customer value.
Turn customer signals into platform leverage: surface recurring patterns to engineering and product teams, influencing the roadmap and enabling reusable capabilities.
Build for scale: Transform one-off solutions into repeatable playbooks, templates, and reference architectures.
Requirements:
4+ years of experience building and operating production software systems.
Strong backend engineering fundamentals and a track record of delivering reliable systems.
Experience integrating APIs and distributed services into real-world infrastructure.
Comfort operating across cloud and containerized environments (AWS, GCP, Kubernetes).
Experience navigating enterprise constraints: authentication, networking, observability, and security reviews.
Ability to take ambiguous problems, define structure, and drive them to resolution.
High ownership and bias for action: you move quickly without waiting for perfect specs.
Clear, structured communicator comfortable engaging with senior technical stakeholders.
Nice-To-Haves:
Experience in forward-deployed solutions, implementation, or customer-facing engineering roles.
Experience deploying AI/ML systems into production environments.
Familiarity with real-time systems (voice, streaming APIs, telephony, low-latency systems).
Experience with on-prem or hybrid infrastructure deployments.
Multilingual fluency or experience supporting customers across international markets and non-English language deployments.
Startup or founder experience.
Experience
4-8 yrs
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