[Hiring] Customer Success Engineer @Deepgram

Role Description

The Customer Success team at Deepgram sits at the intersection of customers, product, and growth. 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.

• 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.
• 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.

Qualifications

• 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.
• 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.
• Demonstrated success identifying and landing expansion in complex enterprise accounts.
• Fluency discussing APIs, integrations, and developer workflows, and troubleshooting L1-style issues.
• Experience engaging both technical stakeholders (developers, architects) and executive buyers (CIO, CTO, VP Engineering).
• Exceptional communication, influence, and relationship-building skills.
• Something you've built — a tool, agent, script, or workflow — that permanently eliminated recurring work.
• An AI-native operating model: specific workflows that structurally depend on AI.

Requirements

• For most people, roughly 7+ years of experience, but the shape of your experience is more important than the exact number.

Nice to Have

• 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).