Staff QE

AlphaSense

3d•$148,350 - $203,550

About The Position

AlphaSense’s Expert Research business helps customers find experts, conduct compliant human- or AI-led interviews, and turn conversations into actionable research. As Staff Quality Engineer, you will be accountable for quality across this portfolio. You will define the testing strategy, close gaps in important customer workflows, and help engineering teams ship faster with confidence. The role works across several engineering teams without a dedicated QE team or manager, so it requires setting direction independently and influencing others.

Requirements

Hands-on end-to-end automation experience with Cypress or Playwright, and willingness to learn the other.
Strong skills in at least one programming language, such as Ruby, TypeScript/JavaScript, Python, Kotlin, or Java, and comfort working in unfamiliar codebases.
Excellent test design skills, including API testing and a deep understanding of testing theory.
Experience with unit and component testing frameworks, such as RSpec or Vitest, and a clear understanding of how test layers fit together.
A track record of using AI tools to accelerate software delivery and testing.
Strong understanding of continuous delivery and release gating.
Experience setting up CI/CD pipelines and using test management systems such as Allure TestOps, as well as 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 skills with technical and non-technical stakeholders.

Nice To Haves

Experience testing complex, workflow-heavy web applications, such as scheduling tools, marketplaces, or admin tools.
Experience with compliance-sensitive products or sensitive data, such as transcripts or restricted content.
Experience evaluating AI or LLM output.
Familiarity with Ruby on Rails or Vue.
BS/MS in a relevant technical field.

Responsibilities

Define the long-term testing strategy for Expert Research, based on Quality by Design and Automation by Default.
Close test coverage gaps in mission-critical and business-critical workflows, including call scheduling, expert sourcing, compliance, transcript review, and client and expert portals.
Build and grow scalable end-to-end automation and determine the appropriate coverage at unit, component, API, and end-to-end layers.
Partner with developers on test planning for new features so automation is ready alongside the code.
Set measurable quality metrics and release gates.
Test AI-powered features, including AI-led interviews and call synthesis, and help define how their output is validated.
Use AI tools to accelerate test design, maintenance, and triage, and demonstrate their use to others.
Coach engineers on shift-left and quality-by-design practices, influencing without direct authority.