Deepgram

Deepgram

Partner Success Engineer (Infrastructure)

USA | Remote

Sponsorship not specifiedDetected 11 days ago
TypeScriptPythonCloud PlatformsDockerKubernetesHelmMachine LearningSalesCustomer SuccessCommunication

About the role

  • 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.
  • 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.

Responsibilities

  • 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 - making Deepgram successful inside the partner's environment and on the partner's hardware and platforms.
  • Lead joint technical validation: scope and run POCs and evaluations that prove Deepgram models on partner infrastructure across self-hosted, on-prem, air-gapped, dedicated, and on-device/edge deployments, including security-sensitive and regulated use cases.
  • 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, and activate partner channels - OEMs, distributors, marketplaces, and cloud/inference providers - to reach their customer base.
  • Lead executive business reviews and joint planning sessions.
  • Support joint go-to-market and co-marketing in partnership with Marketing - joint blogs, one-pagers, PR, and live demos at partner events and industry conferences - to drive awareness and activate the channel.
  • Act as the voice of the partner internally - influencing roadmap (especially deployment, self-hosted, security, and edge), GTM strategy, and the tools we build to support partners.
  • travel to partner sites and events as needed.

Requirements

  • 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.
  • For most people that's roughly 7+ years, but we care more about the shape of your experience than the exact number.
  • Fluency discussing APIs, integrations, and developer workflows, and troubleshooting L1-style issues (no coding required, but genuinely conversant - not hand-waving).

Nice to have

  • Familiarity with GPU/accelerator infrastructure and inference optimization - quantization, model serving, throughput/latency tuning, or benchmarking.
  • Exposure to confidential computing, trusted execution environments, model/weight security, or deployments in regulated industries.
  • Experience with on-device or edge AI deployment across CPU/GPU/NPU targets, model catalogs, or hardware optimization toolchains.
  • You don't need to be a software engineer - just dangerous enough to ship working systems.
  • No coding required, but you're fluent in APIs, containers and orchestration, inference on GPUs/accelerators, and real technical conversations.
  • AI-native operating model - AI is how you work, not a tool you occasionally reach for.
  • Experience engaging both technical stakeholders (developers, platform and ML engineers, architects) and executive buyers (CIO, CTO, VP Engineering).
  • Something you've built - a tool, agent, script, or workflow - that permanently eliminated recurring work.

Benefits

  • Track adoption, usage, health, and expansion to drive outcomes; travel to partner sites and events as needed.

Company info

  • Increasingly, our largest opportunities depend on meeting customers wherever their data and compute live - self-hosted, on-premises, air-gapped, single-tenant dedicated, and at the edge.

This listing is sourced directly from Deepgram's careers page and normalized into a canonical job model.