Security Engineer

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:

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

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

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

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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:

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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.

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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.

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

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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

Deepgram is looking for a Security Engineer to build and automate the technical controls behind our security program. Most of our infrastructure is bare metal in colocation datacenters — GPU-intensive, running containerized workloads on Docker, managed with Ansible, and shipped through CI/CD on GitHub Actions — with AWS used for overflow capacity and a small set of services. Our engineering culture is high-trust and fast-moving. That means controls have to be delivered as code, be reproducible, and produce their own audit evidence — anything that depends on someone remembering to do it manually will not survive.

You will own real surface area: host hardening and configuration management across the fleet, vulnerability and patch management, penetration testing, container security, detection and response, CI/CD and supply chain security, and the engineering work behind our SOC 2, PCI DSS, and ISO 27001 obligations. You will also be expected to use AI and agentic tooling aggressively to punch above your weight on a small team, and to help us secure the AI systems we build and the AI tools we adopt internally.

This is the hands-on technical seat. A GRC and Security Compliance Lead owns policy authorship, security questionnaires, and the auditor relationship; you own the controls themselves and the evidence they generate, and you give that role the technical answers it needs.

This role reports to the Director of Information Security.

Note: as reflected on our published compensation ranges, we are open on level. Strong mid-level and senior candidates are both in scope, and we will calibrate title, scope, and compensation to demonstrated experience.

About Deepgram

Deepgram builds foundational voice AI — speech-to-text, text-to-speech, and voice agent infrastructure — used by enterprises and developers to build production voice applications at scale. Our models are trained and served on our own infrastructure, and we offer hosted, dedicated single-tenant, and self-hosted deployment options so customers can meet their own data residency and retention requirements. Learn more at deepgram.com.

Responsibilities

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Build, deploy, and maintain security controls across our bare-metal fleet and AWS footprint — access management, network segmentation and firewalling, encryption and secrets management, logging and detection coverage, endpoint security, and vulnerability management.

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Own configuration management and host hardening as code with Ansible, so baselines are reproducible across hundreds of Linux hosts and drift is detectable rather than merely documented.

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Secure containerized workloads: Docker image build pipelines, registry scanning, runtime hardening and detection, and secrets management.

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Run vulnerability management end to end — discovery, prioritization by real exploitability rather than raw CVSS, driving remediation with engineering teams, and reporting on it.

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Own patch and update management as a program: the server fleet, the endpoint fleet, base images, OS and package updates, firmware where it matters, and dependency upgrades. Set and hold patch SLAs, track exceptions, and automate the routine cases so they do not depend on anyone remembering.

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Own the penetration testing lifecycle: scoping and vendor selection, scheduling, triaging findings into engineering work with real owners and dates, verifying fixes on retest, and pro