Solutions Engineer, Enterprise
Listed on 2026-06-04
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Software Development
AI Engineer, Cloud Engineer - Software
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 r 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 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.
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.
We move at the pace of AI. Change is rapid, and your day‑to‑day work will evolve 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.
OpportunityYou 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.
LocationThis role is based in New York City, where many of our customers and partners are located. While the role is based in NYC, it is 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.
WhatYou’ll Own
- Customer engineering partnership: embed with customer engineering teams as a trusted technical peer and 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, and serve as an escalation point for complex technical issues…
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