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
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 continuously rather than through manual testing alone
Partner with Engineering, Product, Research, Data, Infrastructure, and DevOps to understand system behavior, dependencies, variations, performance limits, and deployment risks, and to establish appropriate test coverage
Test data ingestion, processing, annotation, and quality-control workflows, validating data integrity, completeness, representativeness, deduplication, leakage, and downstream readiness
Execute staging and production validation, load and reliability testing, cross-browser and customer-workflow testing, and user acceptance testing in partnership with internal stakeholders and customer QA teams
Maintain and improve the test-case repository, automation coverage, test documentation, and release-readiness reporting so teams have a clear view of what was tested, what passed, and what remains risky
Write precise, actionable bug reports with reproducible steps, inputs, parameters, expected and actual results, logs or artifacts, and clear severity; participate in triage and escalate issues when necessary
Help raise the bar through code reviews, test-design reviews, technical discussions, and strong engineering, automation, and QA practices