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Deepgram is the leading Voice AI platform powering the next generation of mission-critical government systems. The company provides real-time APIs for speech-to-text, text-to-speech, and voice agents at scale, serving over 200,000 developers and 1,300+ organizations including Twilio, Cloudflare, and others. Backed by Series C funding, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words.
As Federal Partner Manager, you will build and scale Deepgram's federal partner network from the ground up, working closely with the VP of Federal. This is a builder role owning strategy and execution for named Systems Integrators, Primes, strategic hyperscaler alliances, and channel partners. You will design and drive sell-to, sell-through, and sell-with motions, landing joint solutions inside each partner's delivery and capture organization, and delivering measurable partner-sourced and partner-influenced revenue.
Key responsibilities include: developing end-to-end federal partner strategy with joint value propositions and account plans; driving three distinct motions (embedding Deepgram in SI/prime platforms, standing up repeatable SI-led offerings for agencies, and co-selling into named federal accounts); building measurable partner-sourced pipeline with quarterly/annual targets; creating joint solutions and reference architectures for Defense, Federal Civilian, Intelligence Community, and SLED agencies; designing partner enablement programs including technical certifications, sales plays, and GovCloud environments; and leveraging AI agents and automation to operate at 10x scale of conventional federal alliances teams.
You will work with product, engineering, solutions architects, and partner industry/mission practices to package offerings. The role requires an AI-first mindset—you will build and deploy AI systems (agents, automations, data pipelines) to monitor partner activity, maintain pipeline hygiene, and generate partner-specific collateral. This is not a traditional partner program; it's an AI-native approach to federal GTM reinvention.
