About AlphaSense:
The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content.
The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!
About the Role:
As a Staff Quality Engineer on the Content Portfolio team, you will own and drive test strategy, build automation frameworks, and embed a culture of quality ownership across the engineering organization. Your deep expertise in automation, cloud services, Kubernetes, and modern programming languages will directly shape how we test, release, and deliver reliable software at scale. You will partner closely with developers, product managers, and platform teams to define test requirements, architect quality infrastructure, and ensure AlphaSense ships with confidence at velocity.
You will:
Lead the development of test automation frameworks across UI, API, and GraphQL layers, focusing on reliability, maintainability, and speed
Design and integrate AI evaluation frameworks to assess accuracy, consistency, and reliability of LLM-powered features
Leverage AI-assisted development tools such as Cursor and Claude to accelerate test creation, debugging, and code generation
Lead technical implementation of performance testing and monitoring solutions
Develop custom reporting and analytics tools to provide insights into test coverage, flaky test rates, and quality metrics
Drive adoption of newer testing technologies and approaches
Optimize test execution pipelines for faster feedback in CI/CD environments
Partner with development teams to implement shift-left testing practices and embed quality ownership within teams
Lead root cause analysis for critical issues and drive systematic improvements to prevent recurrence
Participate in code reviews to ensure testability and quality considerations are addressed early
Provide technical mentorship to QE engineers on automation best practices, framework usage, and AI tooling
Desired Skills:
8+ years of hands-on experience in software quality engineering roles with at least 2 years operating at a Staff/Lead level.
Deep proficiency in testing TypeScript/JavaScript and modern frontend ecosystems (React, Webpack, or similar).
Expert-level experience with Playwright or comparable browser automation frameworks (Cypress, Selenium WebDriver) for end-to-end testing.
Strong experience with unit and component testing frameworks such as Vitest, Jest, or React Testing Library.
Proven track record of designing and building test automation frameworks from scratch or significantly evolving existing ones at scale.
Solid understanding of CI/CD systems (GitHub Actions, Jenkins, Buildkite, Gitlab or similar) and how to integrate and optimize test suites within them.
Experience with GraphQL APIs - Writing integration tests, mocking schemas, and validating query/mutation contracts.
Familiarity with performance and load testing tools (k6, Lighthouse, Artillery).
Experience with visual regression testing (Percy, Chromatic, Playwright visual comparisons).
Hands-on experience with Allure or similar test reporting/analytics platforms.
Understanding of AI/ML-powered products and the unique testing challenges they present (non-deterministic outputs, data quality, model evaluation).
Experience in SaaS, fintech, or market intelligence domains.
Track record of contributing to developer experience improvements like test tooling plugins, custom ESLint rules for test quality, documentation-as-code practices.
Familiarity with Docker, Kubernetes, and cloud infrastructure (AWS/GCP).
Familiarity with AI/LLM evaluation frameworks
Hands-on experience with AI-assisted development tools such as Cursor, GitHub Copilot, or Claude for accelerating test authoring, code review, and debugging.
Experience building or configuring MCP (Model Context Protocol) servers