Partner Success Engineer (Infrastructure) - Deepgram

Company Overview

Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box.

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. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words.

Company Operating Rhythm

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.

Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do.

Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.

Our Customer Success team sits at the intersection of partners, product, and growth. We don’t just “manage accounts.” We make Deepgram succeed inside our partners’ environments by combining deep technical expertise, commercial instinct, and an AI-native way of working—and by building the systems that make the whole team’s work compound over time.

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.

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. You’ll own that motion: turning deep technical validation into joint go-to-market, co-sell, and durable channel growth.

Who You Are

You operate at the intersection of three competencies:

• Expert technical consulting: You run demos, guide deployment architecture discussions, troubleshoot integrations, and help partners stand up Deepgram across self-hosted, on-prem, dedicated, and edge environments. You’re fluent in APIs, containers and orchestration, inference on GPUs/accelerators, and real technical conversations.
• Strategic partner management: You build trust from individual developers up to CTOs, own the full partner lifecycle, and turn technical adoption into channel growth across OEMs, distributors, cloud and inference providers, and other multi-party commercial relationships.
• AI-native operating model: AI is how you work. When you hit recurring work, your instinct is to build the system that removes it.

You thrive on bringing definition to ambiguity, forming recommendations rather than staying in open-ended discovery mode, and learning fast.

What You’ll Do

• Serve as the technical advisor and strategic owner for a portfolio of strategic infrastructure partners, engaging stakeholders from developers to CTOs.
• Own the full partner lifecycle: onboarding, adoption, technical enablement, expansion, and advocacy.
• Drive joint adoption through live demos, workshops, deployment architecture guidance, benchmarking, and troubleshooting.
• Lead joint technical validation: scope and run POCs proving Deepgram models on partner infrastructure across self-hosted, on-prem, air-gapped, dedicated, and edge deployments.
• Translate partner challenges into actionable requirements for product and engineering.
• Identify expansion opportunities (cross-sell, upsell, co-sell) in partnership with Sales, and activate partner channels.
• Support joint go-to-market and co-marketing (blogs, one-pagers, PR, live demos at partner events).
• Act as the internal voice of the partner to influence product roadmaps, GTM strategy, and tooling.
• Track adoption, usage, health, and expansion metrics; travel to partner sites and events as needed.
• Build AI tools, agents, and workflows that eliminate recurring work for yourself and the broader team.

What We’re Looking For

• Roughly 7+ years of experience in technical, customer-facing roles (TAM, sales/solutions/deployment engineering, partner CS, implementation, or support) at API-driven, developer-first, infrastructure, or AI companies.
• A track record blending partner ownership with technical depth: solution design, hands-on troubleshooting, and commercial growth.
• Hands-on experience leading demos, POCs, or technical workshops for enterprise partners or customers.
• Conversant fluency with APIs, integrations, and developer workflows.
• Working understanding of containers and orchestration (Docker, Kubernetes/Helm), GPU/accelerator inference, and trade-offs across self-hosted, on-prem, air-gapped, dedicated, and edge deployments.
• Proven success identifying and landing expansion in complex enterprise accounts.
• Strong understanding of partner ecosystems and channel business models (resale, referral, co-selling, OEMs, distributors).
• Experience engaging both technical engineers and executive buyers (CIO, CTO, VP Engineering).
• Excellent communication skills across both technical and business audiences.
• Experience building a tool, agent, script, or workflow that permanently eliminated recurring work.
• An AI-native operating model with workflows structurally dependent on AI.

Nice to Have

• Experience in machine learning, voice AI, cloud infrastructure, or developer-first technologies.
• Familiarity with GPU/accelerator infrastructure and inference optimization (quantization, model serving, latency tuning).
• 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.
• Background in Telephony, CCaaS, or CPaaS (e.g., Twilio, Genesys).
• Working fluency with automation or scripting (Python, TypeScript, workflow tools, or agent frameworks).