At Krisp, we’re building an AI-first Customer Experience (CX) platform to power real-time agent assistance, automation, and post-call intelligence. We’re looking for a Product QA Lead to take ownership of quality assurance across all AI-powered applications, including Noise Cancellation, Accent Conversion, Supervisor Assist, Agent Assist, and the AI Support Agents.

This is a hands-on leadership role where you’ll drive test strategy, design automation systems, and build scalable processes to ensure product quality from day one.

You’ll work closely with product, engineering, AI engineering, and ML research teams to define testing frameworks, catch issues early, and ensure that Krisp’s voice AI products meet enterprise-grade expectations for performance, accuracy, and reliability.

• Lead QA strategy and execution for Krisp CX products, including real-time Agent Assist, Supervisor Assist, and other product directions.
• Build scalable, automated test frameworks to validate LLM, Web, and Desktop UIs, and real-time audio workflows.
• Develop system-level test strategies for AI products, ensuring production-level reliability.
• Partner with engineering leads to define acceptance criteria, edge cases, and failure recovery logic across critical user workflows.
• Define and track key quality metrics, including model accuracy, latency, and UX regressions.
• Collaborate with product managers to design test plans aligned with roadmap priorities, pilot timelines, and field validation efforts.
• Work across teams to ensure tight release cycles with confidence through CI/CD integration, regression suites, and exploratory testing.
• Proactively identify quality risks in early designs and drive mitigation strategies.
• Mentor and scale QA engineers; act as the center of excellence for QA across AI product teams.

• Strong experience leading QA in fast-paced, product-driven environments with a focus on real-time systems or AI-powered tools.
• Hands-on expertise in QA automation using modern frameworks across Web, API, and desktop platforms.
• A systems mindset and ability to define end-to-end test strategy for hybrid products that span AI, Web, and Desktop surfaces.
• Familiarity with LLMs, pipelines, or speech processing workflows—even at the black-box testing level.
• Proven ability to collaborate cross-functionally and influence technical direction from a QA perspective.
• High attention to detail, curiosity, and accountability for delivering polished, production-grade experiences.
• Excellent communication skills—able to clearly document test strategies, share quality insights, and work closely with engineers and PMs.
• Passion for building voice-first, AI-powered user experiences that impact agents, supervisors, and support operations at scale.