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NEXTMOVEFDE careers · United States

Engineering Manager, Console Team (Product-Led Growth Strategy)

Technologies

Rust · LLM APIs · MCP · Elm · Postgres · GPUs · SDK · agentic tooling · voice AI

About Deepgram

Builds speech-to-text, text-to-speech, audio intelligence, and voice-agent APIs for developers and enterprises deploying real-time voice applications at scale.

Series C · 100–200 people

Job description

The full responsibilities and requirements are on the employer’s site.

Open application page
Source and classification

Internal deployment & tooling · Evidence for this classification:

seeking something highly prescriptive with a traditional 9-to-5. Opportunity Deepgram is looking for an Engineering Manager to help drive our product-led growth strategy. Deepgram is the leader in developer-friendly building blocks for language AI—real-time transcription, voice agents, and audio intelligence at scale. As such, this role directly impacts the customer's first impressions of Deepgram's products and uniquely influences their buying decisions. In this role, you will lead a team of frontend and backend engineers who work on our self-serve products like Console, and Product Playground. By partnering closely with Product, Sales, and Marketing, you will execute on the next-generation vision for our self-service platform. In the current wave of AI-native development, developer experience is the product. The best infrastructure wins by being the easiest to trust. What You'll
More from the job description

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. There is no organization in the world that understands voice better than Deepgram. 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 [... source excerpt omitted ...] is the leader in developer-friendly building blocks for language AI—real-time transcription, voice agents, and audio intelligence at scale. As such, this role directly impacts the customer's first impressions of Deepgram's products and uniquely influences their buying decisions. In this role, you will lead a team of frontend and backend engineers who work on our self-serve products like Console, and Product Playground. By partnering closely with Product, Sales, and Marketing, you will execute on the next-generation vision for our self-service platform. In the current wave of AI-native development, developer experience is the product. The best infrastructure wins by being the eas [... source excerpt omitted ...] , help identify the critical paths, and resolve dependencies Hold regular 1-on-1s with direct reports, help them navigate challenges, and coach them for their career development You'll Love This Role If You Have experience working in early stage startups—from building and scaling to going through fundraising Have great communication and leadership skills and the ability to work in a fast-paced environment Have strong practical experience with software architecture and implementation, plus the ability to engage with an engineering team to help build and scale the existing infrastructure Think about LLMs, agents, and model APIs as first-class product primitives—not just add

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