Senior Quality Engineer, Findata

The world’s most sophisticated companies rely on Alpha Sense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, Alpha Sense 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 Alpha Sense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, Alpha Sense 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, Alpha Sense 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!

As we transition into an AI-First Operating Model and move from exploration into execution at scale, we are seeking a seasoned Senior Quality Engineer to join our QE org and lead quality on Fin Data portfolio—spanning financial data generation, delivery, and user-facing experiences across multiple engineering teams.
In this high-impact role, you will be accountable for architecting the quality standards that underpin our next generation of market intelligence. Your remit is to define how we build, test, and operate in an AI-centric ecosystem. You will lead quality initiatives that ensure our engineering workflows—covering everything from complex data pipelines and AI model validation to system observability and agentic search interactions—are robust, scalable, and AI-boosted.

You will be a key leader in establishing "AI-First" as our standard operating procedure, defining the quality gates that enable us to deliver state-of-the-art market intelligence with confidence and precision at scale.

Fluency with AI tools and a proven track record of enabling AI tools to accelerate software delivery and processes.

Proficiency in testing methodologies and deep understanding of the QA domain and theory

Experience with Test Management Systems (e.g., Allure Test Ops)

Excellent test design skills and experience in API testing

Experience with UI test automation frameworks (e.g., Playwright)

Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Kubernetes)

Strong understanding of continuous delivery

Demonstrated ability to operate and set direction autonomously, without a dedicated QE team or manager in place

Experience coaching engineering teams on quality-by-design and shift-left practices, influencing without direct authority

Strong communication skills and ability to collaborate with stakeholders across multiple portfolios

• Strong communication skills and ability to collaborate with stakeholders across multiple portfolios

  Bonus points if you have:

Experience in setting up and configuring CI/CD tools and pipelines

Good understanding of GraphQL

Proven expertise in Performance Engineering (using k6 or similar) and Observability (Open Telemetry/Grafana) to drive data-informed quality decisions

Financial data domain knowledge

BS/MS degree in a relevant technical discipline such as Computer Science, Engineering, or Information Technology

• Define and drive the long-term testing strategy and quality culture for the AI Platform, emphasizing "Quality by Design" and "Automation by Default."
• Define quality metrics and coverage standards, partnering with product and engineering teams to ensure data-driven, measurable, and self-sustaining quality outcomes.
• Grow test coverage through scalable, domain-specific automation and define/maintain complex test datasets, partnering with developers to ensure automation readiness.
• Guide and support test planning for new features, ensuring alignment with acceptance criteria and coverage across unit, integration, and E2E layers.
• Continuously…