Partner Success Engineer – Infrastructure

🕒 Julho 10

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $195.000 - $235.000 / ano

⏰ Tempo Integral

🟠 Sênior

🔴 Especialista

👷 Engenheiro de Infraestrutura

🦅 Patrocina Visto H1B

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👻 Score fantasma 20%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Deepgram

51 - 200 funcionários

Fundada em 2015

💼 Consultoria

🏥 Saúde

📦 Logística

💰 $47.000.000 Series B em 2022-11

Consulting • Healthcare • Logistics

A Deepgram é uma empresa líder em IA de voz que fornece APIs poderosas para aplicações de reconhecimento de fala, síntese de texto para fala e entendimento de linguagem. Sua plataforma permite que os desenvolvedores criem soluções avançadas de IA de voz para casos de uso como centrais de atendimento, transcrição médica, IA conversacional, entre outros. Conhecida por sua precisão inigualável, velocidade e custo-benefício, a tecnologia da Deepgram é confiada por grandes empresas e startups em todo o mundo. Oferecendo capacidades de transcrição em tempo real e altamente precisas, a Deepgram ajuda as empresas a obter insights a partir de dados de voz, tornando-se uma ferramenta essencial para transformar interações de voz.

Descrição

• 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. Your impact is measured by the leverage you create, not just the partners you serve.

🎯 Requisitos

• 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. 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 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 — leading them, not just attending. • Fluency discussing APIs, integrations, and developer workflows, and troubleshooting L1-style issues (no coding required, but genuinely conversant — not hand-waving). • Working understanding of deployment and infrastructure: containers and orchestration (Docker, Kubernetes/Helm), inference on GPUs/accelerators, and the trade-offs across self-hosted, on-prem, air-gapped, dedicated, and edge/on-device deployments — including basic latency, throughput, and benchmarking concepts. • Demonstrated success identifying and landing expansion in complex enterprise or partner accounts. • A strong understanding of partner ecosystems and channel business models — resale, referral, integrations, co-marketing, co-selling — and multi-party commercial dynamics, ideally including hardware/silicon, cloud and inference providers, or OEM/distributor channels. • Experience engaging both technical stakeholders (developers, platform and ML engineers, 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.

🏖️ Benefícios

• Offers Equity

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