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Salary: USD 148,350 - 203,550 / annual
AlphaSense is an AI platform for market intelligence and workflow orchestration used by leading organizations in business and finance. The Expert Research division helps customers find experts, run compliant interviews, and turn conversations into actionable research. This division is growing rapidly with AI at the center of product development and testing.
As Staff Quality Engineer, you will own quality across the Expert Research portfolio without a dedicated QE team or manager reporting to you. You will set testing strategy, identify and close gaps in critical customer workflows, and enable engineering teams to ship faster with confidence. This is an individual contributor role with significant influence across multiple engineering teams.
Key responsibilities include:
- Define long-term testing strategy for Expert Research based on "Quality by Design" and "Automation by Default" principles
- Close test coverage gaps on mission-critical workflows: call scheduling, expert sourcing, compliance, transcript review, and client/expert portals
- Build and scale end-to-end automation, determining appropriate test layers (unit, component, API, E2E)
- Partner with developers on test planning for new features to ensure automation readiness
- Establish quality metrics and release gates for teams to measure and act on
- Test AI-powered features including AI-led interviews and call synthesis; define validation approaches for AI output
- Leverage AI tools to accelerate test design, maintenance, and triage; mentor others on these practices
- Coach engineering teams on shift-left and quality-by-design practices, influencing without direct authority
Requirements:
- Hands-on E2E automation experience with Cypress or Playwright (willingness to learn the other)
- Strong programming skills in at least one language: Ruby, TypeScript/JavaScript, Python, Kotlin, or Java; comfort in unfamiliar codebases
- Excellent test design skills including API testing and deep understanding of testing theory
- Experience with unit and component testing frameworks (RSpec, Vitest, etc.) and understanding of how test layers integrate
- Track record of using AI tools to speed up software delivery and testing
- Strong understanding of continuous delivery and release gating
- Experience with CI/CD pipeline setup, test management systems (Allure TestOps), performance and observability tools
- Proven ability to set direction independently without a QE team or manager
- Experience coaching engineering teams on quality and influencing across multiple teams
- Strong communication with technical and non-technical stakeholders
Bonus qualifications:
- Experience testing complex, workflow-heavy web applications (scheduling, marketplaces, admin tools)
- Experience with compliance-sensitive products or sensitive data handling
- Experience evaluating AI or LLM output
- Familiarity with Ruby on Rails or Vue
- BS/MS in a relevant technical field
