QA Lead Engineer

Company Overview

Deepgram is the leading voice AI platform for developers building speech-to-text (STT), text-to-speech (TTS) and full speech-to-speech (STS) offerings. 200,000+ developers build with Deepgram’s voice-native foundational models – accessed through APIs or as self-managed software – due to our unmatched accuracy, latency and pricing. Customers include software companies building voice products, co-sell partners working with large enterprises, and enterprises solving internal voice AI use cases.

The company ended 2024 cash-flow positive with 400+ enterprise customers, 3.3x annual usage growth across the past 4 years, over 50,000 years of audio processed and over 1 trillion words transcribed. 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.

You’ll be the technical backbone of the QA function—building automation, running tests, and ensuring every release is qualified. As QA Lead Engineer, you’ll directly protect product reliability and customer trust while raising the bar for testing across engineering.

What You’ll Do

• Test Execution & Evaluation: Run daily/weekly test cycles across multiple products and environments

• Automation Ownership: Build, maintain, and extend automated test frameworks integrated into CI/CD pipelines

• Test Case Management: Author, update, and optimize test cases across product lines

• Cross-Product Quality Support: Partner with product squads to enable feature validation and regression coverage

• Release Candidate Signoff: Participate in release readiness reviews and provide test evidence for release evaluation and qualification

• Edge Case & Exploratory Testing: Hunt for failure modes beyond the “happy path