Voice AI Platform · San Francisco
Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.
At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance.
Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.
Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.
Remote · Full-Time · Customer Success
Our Customer Success team — The Heartbeat of Deepgram — sits at the intersection of customers, product, and growth. We don't just "manage accounts." We make Deepgram succeed inside our customers' environments by combining deep technical expertise, commercial instinct, and an AI-native way of working — and by building the systems that make the whole team's work compound over time.
A Customer Success Engineer is a hands-on partner who drives adoption, solves hard technical problems, uncovers expansion, and owns a portfolio of strategic enterprise accounts end to end.
You're not a traditional CSM or Technical Account Manager. You operate at the intersection of three competencies, and you're genuinely strong across all three:
Expert technical consulting — you run demos, guide architecture discussions, troubleshoot integrations, and help customers deploy AI-driven solutions. No coding required, but you're fluent in APIs, developer workflows, and real technical conversations.
Strategic account management — you build trust from individual developers up to CTOs, own the full customer lifecycle, and turn technical adoption into commercial growth.
AI-native operating model — AI is how you work, not a tool you occasionally reach for. When you hit recurring work, your instinct is to build the system that removes it.
You may have been a Technical Account Manager, Solutions or Sales Engineer, Forward Deployed Engineer, Implementation Engineer, strategic CSM, or Product Manager. Whatever your path, you're probably strongest in one or two of these competencies — but you can demonstrate all three, and you're eager for a role where you deploy them concurrently.
You thrive on bringing definition to ambiguity. You form a point of view and bring a recommendation rather than staying in open-ended discovery mode. You're comfortable operating outside your comfort zone, you question the status quo, and you learn fast.
Serve as the technical advisor and strategic owner for a portfolio of enterprise accounts, partnering with everyone from developers to CIOs and CTOs.
Own the full customer lifecycle: onboarding, adoption, technical enablement, expansion, and advocacy.
Drive adoption through live demos, workshops, architecture guidance, troubleshooting, and best-practice recommendations — making Deepgram successful inside the customer's environment.
Run discovery continuously: surface customer problems, understand their business impact, and translate them into actionable requirements for product and engineering.
Identify and scope expansion (cross-sell, upsell, multi-product) in partnership with Sales, and lead executive business reviews and joint planning sessions.
Act as the voice of the customer internally — influencing roadmap, GTM strategy, and the tools we build to support customers.
Track adoption, usage, health, and expansion to drive outcomes; travel to customer sites as needed.
Operate AI-first by default, and build tools, agents, and workflows that eliminate recurring work for you and the broader CS team. Your impact is measured by the leverage you create, not just the accounts you serve.
Significant experience in technical, customer-facing roles — TAM, sales/solutions engineering, enterprise CS with a strong technical focus, implementation, or forward-deployed work — at API-driven, developer-first, or AI companies. For most people that's roughly 7+ years, but we care more about the shape of your experience than the exact number.
A track record that blends customer ownership with technical depth: solution design, hands-on troubleshooting, and commercial growth.
Hands-on experience running demos, POCs, or technical workshops with enterprise customers — leading them, not just attending.
Demonstrated success identifying and landing expansion in complex enterprise accounts.
Fluency discussing APIs, integrations, and developer workflows, and troubleshooting L1-style issues (no coding required, but genuinely conversant — not hand-waving).
Experience engaging both technical stakeholders (developers, architects) and executive buyers (CIO, CTO, VP Engineering).
Exceptional communication, influence, and relationship-building — concise and structured, across technical and business audiences.
Something you've built — a tool, agent, script, or workflow — that permanently eliminated recurring work. In your application, tell us what it was, what it replaced, and what it's still doing today.
An AI-native operating model: specific workflows that structurally depend on AI, and a clear account of how you'd rebuild them if those tools disappeared tomorrow.
Experience in machine learning, voice AI, cloud infrastructure, or developer-first technologies.
A background spanning solutions engineering, TAM, or L1 support alongside CS responsibilities.
Working fluency with automation, scripting, or agent-building (Python, TypeScript, workflow tools, agent frameworks, or equivalent). You don't need to be a software engineer — just dangerous enough to ship working systems.