Solutions Engineer, Enterprise

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.

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.

You deploy Deepgram’s voice AI platform into complex restaurant environments and make it work in the real world. This role sits at the intersection of engineering, product, and customer systems, partnering closely with customer leadership and technical stakeholders to bring ambitious deployments to life.

You embed with enterprise restaurant brands and restaurant technology partners, learn their systems deeply, and integrate our platform into the core of their operations. Along the way you write code, debug production issues, and adapt the platform to real world constraints. You operate as a trusted technical partner to both customer leadership and engineering teams, ensuring deployments move quickly and deliver meaningful business outcomes.

You turn real world deployments into leverage for the entire platform by identifying patterns across customers, shaping product improvements, and building the tooling, reference architectures, and playbooks that make each new deployment faster, more reliable, and easier to scale across large restaurant fleets and technology ecosystems.

The mission of this role is to ensure every enterprise deployment of Deepgram for Restaurants works like magic — technically flawless and delivering measurable value from day one.

This role is based in New York City, where many of our customers and partners are located. Being close to them helps us move quickly and stay connected to their needs. While the role is based in New York City, this would still be a remote-first opportunity, as we do not have an office local to the area.

This role also includes up to 50% travel to meet with customers, support sales engagements, and participate in key onsite interactions

• Customer engineering partnership: Embed with customer engineering teams as a trusted technical peer. Lead technical discovery and solutioning for prospects and customers.

• Technical integration and deployment: Own the end-to-end technical implementation of Deepgram’s voice AI platform for enterprise customers — from scoping and architecture through go-live and optimization.

• Configuration and customization: Adapt and configure Deepgram’s platform to meet each customer’s unique operational requirements — menu structures, ordering flows, POS integrations, edge cases, and everything in between.

• Production excellence: Monitor, troubleshoot, and resolve technical issues in live deployments. Serve as an escalation point for complex technical issues when necessary.

• Deployment infrastructure leadership: Codify patterns into tools, playbooks, reference architectures, and building blocks the broader team can use for other deployments and customers.

• Feedback loop to product and engineering: Translate real-world deployment challenges into actionable requirements for Deepgram’s product and engineering teams. You are the voice of the customer inside the building.

• You are hands-on. You write code, read logs, and ship fixes — you don’t just coordinate. When a customer has a technical problem, you roll up your sleeves and solve it.

• You operate with extreme ownership and urgency. You treat every customer deployment as if your name is on the product.

• You partner closely with Sales, Product, and Engineering, but you are just as comfortable on a customer’s Slack channel walking their team through an API integration.

• Technical depth: You are an excellent software engineer. You are comfortable working across APIs, SDKs, webhooks, cloud infrastructure, and customer tech stacks. You use AI coding tools to move fast and multiply your output.

• Customer obsession: Deep, personal commitment to your customers’ technical success. You take their problems home with you. You are not satisfied until the deployment is bulletproof.

• High slope: Learns fast, adapts quickly, and stays effective in ambiguity without needing constant structure. You figure things out and move forward. You are excited to get your hands dirty solving gritty technical problems over sexy ones.

• Communication and trust: Able to build deep credibility with both technical and non-technical stakeholders on the customer side. You are calm under pressure and relentlessly reliable.

• Experience with voice AI, speech-to-text, NLP, or conversational AI systems.

• Previous early-stage startup or founder-led environment experience — you thrive in environments where you wear many hats and build from zero.

• Previous experience embedded within a large enterprise customer’s product deployment.

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