Lead Quality Engineer
Recruiting From Scratch•San Francisco, CA
•Remote
About The Position
Our client is building one of the leading enterprise conversational AI platforms, powering AI voice agents for customer service at scale. Their platform is already deployed with major enterprise brands including DoorDash, Sunrun, and AAA, and has processed over a billion minutes of customer conversations in production environments. The company is entering a major scaling phase as enterprise demand for AI-native customer support accelerates. They are focused on building AI agents capable of handling highly dynamic, real-world customer interactions with quality levels approaching or exceeding human support teams. This is an opportunity to join a rapidly growing AI company backed by over $113M in funding, where you’ll help define how quality engineering operates for modern conversational AI systems.
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
Nice To Haves
- 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
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
Benefits
- Competitive equity package
- Fully remote across US or Canada
- Visa sponsorship and H1B transfers supported
- Opportunity to shape AI-native quality engineering at scale
- Leadership growth path into people management
- High ownership and autonomy across QA strategy and tooling
- Work on cutting-edge conversational AI systems in production
- Backed by $113M in funding with strong enterprise traction
- Exposure to large-scale enterprise AI deployment challenges
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
