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Software Test Engineer

Job in Northern, Floyd County, Kentucky, USA
Listing for: Deepgram
Full Time position
Listed on 2026-08-30
Job specializations:
  • Software Development
    AI QA / Validation Engineer
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Location: Northern

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 e 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.

The Opportunity

Deepgram is looking for a Software Test Engineer to design, build, and maintain automated test frameworks and exploratory test suites across our products, models, APIs, and data platforms. You enjoy breaking systems, probing edge cases, testing real-world and adversarial inputs, and automating repeatable validation so regressions are caught quickly.

You translate product requirements and model metrics into automated regression tests, evaluation pipelines, data-quality gates, load tests, and release criteria. You partner with QA, Research, Product, Data, and Engineering to plan testing, execute human and automated evaluations, support user acceptance testing, and communicate risks clearly.

When you find an issue, you provide precise reproduction steps, inputs, parameters, expected and actual results, and supporting data. What gets you excited? Building scalable automation that gives Deepgram confidence that its products, models, and data workflows work reliably for customers.

What You'll Do
  • Define and execute well-designed test plans across Deepgram's products, APIs, SDKs, model-powered features, and data platforms, ensuring production software is robust, reliable, and performs well.

  • Design, build, and maintain automated test suites and frameworks for functional, integration, end-to-end, regression, API, browser, and service-level testing across batch and streaming workflows.

  • Translate product requirements and customer acceptance criteria into clear test strategies, repeatable test cases, and enforceable release gates.

  • Build and maintain representative, customer-focused, and adversarial test datasets, fixtures, and test environments that exercise real-world inputs, edge cases, failure modes, and system limits.

  • Validate model-powered behavior—including speech-to-text, text-to-speech, and other AI features—using appropriate metrics, expected outputs, human review, and regression coverage, while partnering with Research and model-evaluation specialists as needed.

  • Build testing infrastructure, including test harnesses, reusable scripts, test-data tooling, result-aggregation pipelines, dashboards, and visualizations that make quality signals easy to understand and act on.

  • Integrate automated tests, quality checks, canaries, and release validation into CI/CD so regressions are detected…

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