Level

Deepgram

Senior Data Intelligence Engineer

Deepgram is hiring a Senior Data Intelligence Engineer for a remote role open to applicants in United States. It pays $165k-$220k a year and Level rates it ; you can apply on Deepgram.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • This is listed as a remote role.
  • The posting mentions Sierra, Decagon and Python among its tools and skills.
  • Level classes it as a senior role.
  • Deepgram has 80 other open roles on Level.

AI in this role

Build the data intelligence and API nervous system for voice AI foundation models at Deepgram.

sierradecagonpythonapis
ragai-agentsspeechdata-engineeringdecision-intelligenceapi-development
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 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.

Company Operating Rhythm

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.

About Deepgram

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.

The Role

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.

Key Responsibilities

  • 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.

Requirements

  • 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.

Bonus Points

  • 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.

Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.

How we rate this

Senior Data Intelligence Engineer at Deepgram rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsSpeechData EngineeringDecision IntelligenceAPI DevelopmentSierraDecagon

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. What have you built with speech recognition or text-to-speech, and where did it break?
  4. Tell me about a project where data engineering was part of your work. What did you do?
  5. Tell me about a project where decision intelligence was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: RAG, AI agents, Speech, Data Engineering, and Decision Intelligence. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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