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Open nowPosted 147 days ago

Lead Quality Engineer

Recruiting from Scratch2 open roles

Where
Remote, San Francisco, CA
Work mode
Remote
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Your applicationOpen nowLead Quality EngineerRecruiting from Scratch · Remote, San Francisco, CA

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Share of postings closed within
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  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 147 days ago

The posting

Who is Recruiting from Scratch:

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire.

Lead Quality Engineer

Location: Remote (US or Canada) Company Stage of Funding: Series B Office Type: Remote Salary: $160,000 – $220,000 Base + Competitive Equity Visa: Open to H1B transfers / sponsorship support available

Company Description

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.

What You Will Do

  • 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

Ideal Candidate Background

  • 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

Strong Signals

  • 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

Compensation and Benefits

  • Base salary: $160,000 – $220,000
  • 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

Why Join

This is an opportunity to help define what quality engineering looks like in the era of conversational AI and LLM-powered systems.

You’ll work directly on production AI systems handling millions of real-world customer conversations while building the testing infrastructure, automation tooling, and validation frameworks that power scalable enterprise AI deployments.

If you enjoy solving ambiguous engineering problems, designing AI-native testing systems, influencing cross-functional quality culture, and operating with high ownership in fast-moving environments, this role offers exceptional impact and technical leverage.

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