Solutions Engineer

Cartesia • San Francisco, CA

8d • Onsite

About The Position

Our mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.
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 our first Solutions Engineer to help turn Cartesia’s voice AI infrastructure into enterprise adoption.
Our customers are building real-time voice agents, call automation systems, and AI workflows that depend on low latency, reliability, and production-grade integration.
As a Solutions Engineer, you will partner closely with Account Executives to lead the technical side of strategic deals — from initial discovery through proof-of-concept and technical validation.
You will operate at the intersection of engineering and go-to-market, translating customer workflows and infrastructure constraints into clear architectural paths forward.
This is a high-agency, hands-on role. You’ll write code, build demos, prototype integrations, and run technical deep dives with engineering leaders. You won’t inherit a mature playbook — you’ll help build it by creating demo environments, documentation, and repeatable processes that scale as we grow.
Solutions Engineers are critical to our growth: deals close because the architecture is sound, the integration works, and the customer trusts us to power real-time systems in production.

Requirements

• 3–7+ years of experience in Solutions Engineering, Sales Engineering, or developer-facing technical roles at a high-growth B2B SaaS or infrastructure company.
• Strong engineering foundation — you can write and debug code (Python preferred), understand APIs deeply, and integrate technical products into real-world systems.
• Demonstrated ability to scope and execute POCs end-to-end — gathering requirements, building working integrations, and presenting results clearly.
• Comfort discussing cloud and containerized environments (AWS, GCP, Kubernetes), including deployment models, scaling assumptions, and performance tradeoffs.
• Proven ability to influence executive and senior technical stakeholders — translating complex technical concepts into clear business value.
• Excellent communicator who can move fluidly between backend engineers, ML teams, and executive audiences in the same conversation.
• Customer-first mindset — strong discovery skills and the ability to turn ambiguous requirements into structured technical solutions.
• High agency and proactive ownership — you pick up missing knowledge quickly and drive problems to resolution.

Nice To Haves

• Hands-on experience with voice AI, speech systems (ASR/TTS), or real-time/streaming architectures.
• Experience working with AI/ML APIs, LLM-based systems, or real-time inference pipelines.
• Prior experience as a software engineer or in a deeply technical role before moving into a customer-facing position.
• Experience supporting enterprise deployments across VPC or on-prem environments.
• Familiarity with developer-led or product-led growth (PLG) motions and technical buyer personas.
• Experience as an early or founding Solutions Engineer at a startup

Responsibilities

• Own the technical sales cycle – Lead discovery, architecture discussions, API deep dives, and integration planning across strategic enterprise deals.
• Deliver tailored, high-impact demos – Translate Cartesia’s voice AI into customer-specific workflows that reflect real latency and infrastructure constraints.
• Design and deliver high-impact proofs-of-concept –Scope and test integrations that confirm performance, batching, throughput, and deployment assumptions before contracts are signed.
• Act as a trusted technical advisor – Build credibility with engineering and product leaders by understanding their stack and real-time system requirements.
• Lead infrastructure conversations – Reason through GPU sizing, scaling models, cloud vs. on-prem tradeoffs, and deployment patterns for voice and real-time AI systems.
• Unblock pre-sale integrations – Debug API usage, prototype workflows, and resolve technical objections that would otherwise stall momentum.
• Translate field signal into product leverage – Surface recurring integration patterns, performance gaps, and feature needs to Engineering and Product.
• Build the SE foundation – Create reusable demo environments, documentation, and playbooks that scale our enterprise motion.
• Support strategic deals – Work closely with Account Executives and founders as a technical co-pilot in complex, multi-stakeholder sales cycles.

Benefits

• Lunch, dinner and snacks at the office
• Fully covered medical, dental, and vision insurance for employees
• 401(k)
• Relocation and immigration support
• Your own personal Yoshi

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed