Lead Quality Engineer

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. They are seeking a Lead Quality Engineer to define and lead quality engineering strategies for enterprise conversational AI products, ensuring high standards and scalable testing practices. The role involves mentoring a team, improving automation frameworks, and collaborating with cross-functional teams to enhance quality in AI-native systems.

Responsibilities:

• Lead company-wide quality engineering strategy across conversational AI products and delivery systems
• Define scalable QA standards, testing practices, and release validation processes
• Build and evolve AI-native testing workflows for conversational and voice AI systems
• Design testing strategies for non-deterministic AI systems including hallucinations, context drift, and probabilistic outputs
• Own platform-level validation approaches across AI agents, integrations, workflows, and deployments
• Build and improve automation frameworks, test infrastructure, and CI/CD quality gates
• Use AI tooling to accelerate validation, generate edge-case coverage, and improve test scalability
• Develop tooling for conversation simulation, replay analytics, and voice AI testing workflows
• Lead and mentor a team of QA engineers while raising the technical quality bar across the organization
• Partner closely with Product, Engineering, and Delivery teams to embed quality early in the SDLC
• Improve bug triage, release readiness, and platform reliability processes
• Build scalable feedback loops using customer insights, A/B testing, internal dogfooding, and production analytics
• Drive cross-functional quality initiatives across engineering and customer delivery organizations
• Help transition the organization from manual QA practices toward AI-native quality engineering systems
• Influence testing strategy and quality culture across multiple teams without formal authority

Requirements:

• 8–12 years of experience in QA, Quality Engineering, or SDET roles
• Experience leading quality initiatives across multiple engineering or product teams
• Strong automation engineering background with modern testing frameworks
• Experience testing conversational AI, voice AI, or LLM-powered systems
• Strong AI tooling fluency using tools like Claude, ChatGPT, Cursor, or agentic workflows
• Experience building scalable automation infrastructure and CI/CD quality systems
• Strong technical coding ability in TypeScript, JavaScript, or Python
• Experience designing QA strategies for non-deterministic systems
• Strong cross-functional communication and stakeholder influence skills
• Comfortable operating in ambiguous, fast-moving startup environments
• Hands-on builder mentality with strong ownership orientation
• Experience balancing strategic quality leadership with direct execution
• Customer-facing or delivery-oriented background is a strong plus
• Interest in growing into people management leadership over time
• Experience testing voice AI, chatbot systems, or conversational AI platforms
• AI-native QA engineering experience
• Experience with LLM evaluation, RAG testing, or agentic AI systems
• Built AI-driven QA tooling or automation systems
• Strong Playwright, Selenium, or modern automation framework expertise
• Experience building CI/CD validation pipelines
• Experience with release engineering and platform-level testing systems
• Strong understanding of hallucinations, probabilistic behavior, and edge-case testing
• Background in customer-facing delivery or implementation organizations
• Experience influencing engineering quality standards across multiple teams
• Automation-first mindset versus manual QA orientation
• Experience scaling QA organizations in high-growth startups
• Ability to mentor and elevate junior QA engineers
• Strong product intuition and customer empathy
• Comfortable working cross-functionally without heavy process structures
• Experience using AI tools to improve testing coverage and engineering productivity