About the Role:

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 FinData 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.

Who You Are:

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

• Deep knowledge in at least one of the following programming languages: Kotlin, Python, JavaScript, or Java

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

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

• 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

  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 (OpenTelemetry/Grafana) to drive data-informed quality decisions

• Financial data domain knowledge

• Experience testing backend/data pipeline

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

What You’ll Do:

• 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 improve and streamline testing processes; perform targeted exploratory testing to discover risks, inform automation, and validate model outputs.
• Coach and mentor engineers on sustainable, scalable quality practices, serving as a strategic partner to ensure delivery standards are met through rigorous release gates.