[Hiring] Partner Success Engineer @Deepgram

Role Description

A Partner Success Engineer, Infrastructure is a hands-on customer success representative who drives joint adoption, solves hard technical problems, uncovers expansion, and owns a portfolio of strategic infrastructure partners end to end. This is a specialized seat focused on the silicon, hardware, cloud, inference, and security platforms that Deepgram’s voice AI runs on.

• Serve as the technical advisor and strategic owner for a portfolio of strategic infrastructure partners, engaging everyone from developers and platform/ML engineers to CIOs and CTOs.
• Own the full partner lifecycle: onboarding, adoption, technical enablement, expansion, and advocacy.
• Drive joint adoption through live demos, workshops, deployment architecture guidance, benchmarking, troubleshooting, and best-practice recommendations.
• Lead joint technical validation: scope and run POCs and evaluations that prove Deepgram models on partner infrastructure.
• Run discovery continuously: surface partner problems, understand their business impact, and translate them into actionable requirements for product and engineering.
• Identify and scope expansion (cross-sell, upsell, multi-product, co-sell) in partnership with Sales.
• Support joint go-to-market and co-marketing in partnership with Marketing.
• Act as the voice of the partner internally, influencing roadmap and GTM strategy.
• Track adoption, usage, health, and expansion to drive outcomes.
• Operate AI-first by default, building tools, agents, and workflows that eliminate recurring work.

Qualifications

• Significant experience in technical, customer-facing roles — TAM, sales/solutions/deployment engineering, partner or enterprise CS with a strong technical focus.
• A track record that blends partner or customer ownership with technical depth.
• Hands-on experience running demos, POCs, or technical workshops with enterprise partners or customers.
• Fluency discussing APIs, integrations, and developer workflows.
• Working understanding of deployment and infrastructure: containers and orchestration, inference on GPUs/accelerators.
• Demonstrated success identifying and landing expansion in complex enterprise or partner accounts.
• A strong understanding of partner ecosystems and channel business models.
• Experience engaging both technical stakeholders and executive buyers.
• Exceptional communication, influence, and relationship-building skills.
• An AI-native operating model with specific workflows that structurally depend on AI.

Requirements

• Experience in machine learning, voice AI, cloud infrastructure, or developer-first technologies.
• Familiarity with GPU/accelerator infrastructure and inference optimization.
• Exposure to confidential computing, trusted execution environments, or deployments in regulated industries.
• Experience with on-device or edge AI deployment across CPU/GPU/NPU targets.
• Telephony / CCaaS / CPaaS background.
• A background spanning solutions/deployment engineering, TAM, or L1 support alongside CS or partner responsibilities.
• Working fluency with automation, scripting, or agent-building.