Partner Success Engineer

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.
• Track adoption, usage, health, and expansion to drive outcomes; travel to partner sites and events as needed.
• Operate AI-first by default, and build tools, agents, and workflows that eliminate recurring work for you and the broader team.

Requirements

• Significant experience in technical, customer-facing roles — TAM, sales/solutions/deployment engineering, partner or enterprise CS with a strong technical focus, implementation, or support — at API-driven, developer-first, infrastructure, or AI companies (roughly 7+ years).
• A track record that blends partner or customer ownership with technical depth: solution and deployment design, hands-on troubleshooting, and commercial growth.
• Hands-on experience running demos, POCs, or technical workshops with enterprise partners or customers.
• Fluency discussing APIs, integrations, and developer workflows, and troubleshooting L1-style issues (genuinely conversant).
• Working understanding of deployment and infrastructure: containers and orchestration (Docker, Kubernetes/Helm), inference on GPUs/accelerators, self-hosted/on-prem/edge environments.

Nice-to-Haves

• Background in infrastructure, platform, or hardware ecosystems.
• Experience with silicon, hardware, cloud, inference, and security platforms.
• Strong across technical consulting, strategic partner management, and AI-native operating model.
• Eagerness to build systems that remove recurring work and operate outside comfort zone.