Forward-Deployed Engineer (FDE), Strategic Accounts

Company Overview

Deepgram is bringing the world’s most natural interface, voice, to the technology we use every day. Our speech models and real-time infrastructure power AI systems that keep up with the way people actually speak. More than 5,000 organizations run conversational voice AI on Deepgram in production, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Cresta, Granola, and Jack in the Box.

The Deepgram Voice Agent Platform brings together speech-to-text, text-to-speech and speech-to-speech, with voice-native foundation models available through cloud APIs or self-hosted and on-premises deployments. Built for accuracy, low latency and cost efficiency, Deepgram makes high-quality voice experiences practical to build and run at scale. More than 650,000 developers have used Deepgram to process more than 200,000 years of audio. Every day, more of the world’s conversations with AI run on our models.

Operating Principles:

Deepgram is a research company that productizes as fast as possible. Four Operating Principles shape how we think, decide, and work together:

• Compress before you communicate. You think it through first, then lead with the bottom line.

• Resist entropy. You question what already exists before adding more process or tools.

• Solve the category. You fix recurring problems at the source, not one case at a time.

• Work at the frontier. You go after problems no one has solved yet.

We look for people who already work this way, and these principles shape how we grow and evaluate our team.

AI-First by Default

We build AI that millions of people talk to, and we run the company the same way. AI is how we centralize work here, and is core to how we operate.

That means more than using the tools. We expect you to:

• Build, not just use. Design your own workflows and agents, and use AI to remove whole categories of work instead of doing the same work faster.

• Own the output. AI can speed up the work. It doesn’t make anyone less accountable for it. You understand, verify, and stand behind everything you share, including what an agent produces for you.

• Spend the time you get back at the frontier. The capacity AI creates goes toward problems no one has solved yet.

• Keep pace. Models and tools change every month, and so will your work. You adopt what’s new quickly and drop what no longer earns its place.

We judge AI by what it helps you deliver and whether you stand behind the result, not by how often you use it. In interviews, expect to walk us through a workflow you built and where you drew the line between AI and your own judgment.

The Opportunity

Most engineering roles ask you to build the platform. This one asks you to build everything between the platform and a customer's success: the solutions, integrations, and tooling that run in production for some of the largest enterprises in the world.

Deepgram is seeking Forward-Deployed Engineers for our strategic accounts. You'll embed with one strategic customer at a time, working directly with their technical and business teams, alongside Deepgram's core research teams. Today's engagements center on leading restaurant enterprises and restaurant technology partners (we already partner with several of the world's leading restaurant brands), and the examples in this posting come from that work.

As a Forward-Deployed Engineer, you'll take Deepgram's voice AI platform the last mile. That means production-scale integrations with the systems that your customer actually runs on (today, that's point of sale, loyalty, payment gateways, and customer data platforms), voice agents that take live orders from customers every day, and everything in between: the tooling, prompt engineering, and evaluation work that bridges what Deepgram offers today and what makes your customer successful tomorrow.

Forward-deployed means you do this work with your customer, not just for them. You'll be on site regularly, embedded with their technical team, and close enough to the business to see problems before they become escalations. You'll also have a senior Forward-Deployed Engineer alongside you, reviewing your work before it ships and bringing you into customer meetings. And the platform is not a fixed product that you implement. When your customer needs a capability that the platform does not offer yet, you'll be the one who proves what it should do next, and what you build and learn in the field becomes part of Deepgram's offering for every customer after yours.

About Forward-Deployed Engineering at Deepgram

Forward-Deployed Engineering is how Deepgram embeds with its most strategic accounts. You'll fully deploy into a dedicated account pod (a small, cross-functional team built around one strategic customer) for a defined stretch, working inside of that account's day to day with a high degree of autonomy. Full deployment means exactly that: while you're deployed, your pod's account is your only customer assignment, with no time split across other accounts or teams. Your work directly shapes how some of the world's largest brands put voice AI in front of their customers.

Forward-Deployed Engineers are part of our broader Applied Engineering team, which serves as the technical interface between Deepgram and our customers across their entire journey (it combines what other companies split into Forward-Deployed Engineering, Sales Engineering, Solutions Architecture, Implementation, and Technical Support). Applied Engineering is your home team and your growth path. You'll be hired into the Applied Engineer position, which has a single growth ladder from Associate through Principal, and you'll grow proficient across multiple roles over time. The pod is where you're deployed; Applied Engineering is where you grow.

What You'll Do

• Build and ship whatever the solution needs, whether that's an end-to-end service, an integration, internal tooling, or agent and prompt engineering

• Design, develop, and maintain production-scale integrations with the third-party systems that your customer runs on (in today's pods: point of sale, loyalty, payment gateways, customer data platforms)

• Spend regular time on site with your customer, working directly with their technical and business teams

• Monitor, debug, and optimize what you ship in production, including some of the hardest audio environments in voice AI (noisy, multi-mic, drive-thru)

• Work with our research and product teams to push the platform where your customer needs it to go, and feed what you learn in the field back into the product

• Test changes against live production data and measure whether they move accuracy, latency, and throughput

Time Allocation

• Embedded customer delivery (60-80%) — Deployments, integrations, and technical problem-solving with your account, plus turning what the field teaches you into reusable solutions, automation, and documentation. Where you sit in that range depends on where your engagement is in its cycle.

• Scoping and expansion support (10-25%) — Joining detailed solution scoping, shaping statements of work so that what gets promised can be built, and surfacing the expansion opportunities that you spot from inside of the account. Discovery and demos belong to a pre-sales Applied Engineer in your pod; you'll take parts of that work when the account needs it and hand it back when delivery peaks.

• Internal collaboration (~15%) — Product feedback, knowledge sharing, and contributing to Applied Engineering strategy.

The delivery and scoping buckets trade against each other: at the peak of an engagement, delivery takes the scoping share.

The On-Site Expectation

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