Inferred from the employer’s wording in this job description. These role-level signals are separate from the company-wide employee-review scores below.
Voice AI Platform · San Francisco
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.
Deepgram is the foundational AI company for voice. We build the models that allow machines to hear, understand, and speak to humans with zero latency. As we scale our usage-based economy, we are building the "Intelligence Layer"—a system of autonomous agents that monitor, reason, and act on our data to drive NRR and operational excellence.
Reporting to the Head of Decision Intelligence, you are the founding engineer of the Data Intelligence team. While the Head of Data sets the strategic "Brain" of the company, you build the nervous system. You are not building legacy dashboards; instead you are building the API-based tools, dbt models, and semantic layers that allow AI agents to navigate our data environment autonomously.
Semantic Layer Architecture: Build and maintain high-fidelity dbt and SQL models that serve as the "ground truth" for our complex, usage-based revenue models.
Agent Tooling & Integration: Develop the tools and permissions frameworks that allow "Analyst Agents" to query Athena, correlate Salesforce churn signals, and identify API latency issues.
Infrastructure Evolution: Serve as the technical bridge to the Engineering/Infra team to ensure our data contracts are "agent-ready" and highly reliable.
The "Unlock Audio Intelligence" Project: Partner with the Head of Data to ingest thousands of hours of internal calls using Deepgram’s own models, turning unstructured audio into queryable insights for GTM teams.
Automation Obsession: Maintain a culture where manual, repetitive SQL tasks are viewed as automation bugs to be solved with code and agents.
Experience: 5+ years in high-growth Data or AI Engineering roles.
AI-Native Technical Skills: Mastery of SQL and Python (production-grade) with a proven track record of building RAG or Agentic systems on top of structured data.
Usage-Based SaaS Fluency: Familiarity with the metrics of an API-first business, such as consumption patterns, gross margins, and NRR.
Builder Mindset: Comfort with "work-in-progress" infrastructure and the ability to turn messy, siloed data into high-impact business logic.
Prior experience as a Software Engineer or Data Engineer.
Experience with real-time billing and consumption systems.
Contributions to open-source data or AI projects.