Senior Quality Engineer (Findata)

Role Overview

You will lead quality initiatives for AlphaSense’s FinData portfolio and the AI Platform. The role focuses on defining a long-term testing strategy and building a quality culture that is data-driven, measurable, and self-sustaining.

Key Missions

• Architect quality standards for next-generation market intelligence in an AI-centric ecosystem.
• Drive quality for engineering workflows so they are robust, scalable, and “AI-boosted.”
• Establish “AI-First” as a standard operating procedure.
• Define and run the long-term testing strategy for the AI Platform, emphasizing:
  • Quality by Design
  • Automation by Default
• Coach and mentor engineers to adopt sustainable, scalable quality practices and improve/streamline testing processes.

Responsibilities

• Lead quality initiatives without a dedicated QE team/manager, operating autonomously and setting direction.
• Coach engineering teams on shift-left and quality-by-design practices, influencing without direct authority.
• Continuously improve testing processes and ensure quality outcomes are data-informed.

Requirements

• Experience with UI test automation frameworks (e.g., Playwright).
• Strong understanding of continuous delivery.
• Experience with test management systems (e.g., Allure TestOps).
• Strong test design skills and experience with API testing.
• Deep knowledge in at least one: Kotlin, Python, JavaScript, or Java.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Kubernetes).
• Fluency with AI tools, with evidence of enabling AI tooling to accelerate delivery.
• Proficiency in testing methodologies and deep understanding of the QA domain.
• Experience setting up and configuring CI/CD tools and pipelines.
• Proven expertise in Performance Engineering (e.g., k6) and Observability (OpenTelemetry/Grafana) to drive data-informed quality decisions.
• Understanding of GraphQL.
• Financial data domain knowledge.
• Experience testing backend/data pipelines.
• Strong communication and stakeholder collaboration across multiple portfolios.

Education

• BS/MS in a relevant technical discipline (e.g., Computer Science, Engineering, Information Technology).