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AlphaSense is seeking a Senior Quality Engineer to lead quality initiatives for the FinData portfolio as the company transitions to an AI-First Operating Model. You will be accountable for architecting quality standards across financial data generation, delivery, and user-facing experiences spanning multiple engineering teams.
In this high-impact role, you will define how the organization builds, tests, and operates in an AI-centric ecosystem. Your responsibilities include establishing quality gates for complex data pipelines, AI model validation, system observability, and agentic search interactions. You will lead quality initiatives ensuring engineering workflows are robust, scalable, and AI-boosted, while establishing "AI-First" as the standard operating procedure.
Key responsibilities:
- Define and drive long-term testing strategy and quality culture, emphasizing "Quality by Design" and "Automation by Default"
- Define quality metrics and coverage standards in partnership with product and engineering teams
- Lead quality initiatives across the FinData portfolio spanning multiple engineering teams
- Coach engineering teams on quality-by-design and shift-left practices, influencing without direct authority
- Operate autonomously to set direction and establish quality standards
- Collaborate with stakeholders across multiple portfolios
Required qualifications:
- Fluency with AI tools and proven track record of enabling AI to accelerate software delivery
- Deep knowledge in at least one programming language: Kotlin, Python, JavaScript, or Java
- Proficiency in testing methodologies and deep understanding of QA domain and theory
- Experience with Test Management Systems (e.g., Allure TestOps)
- Excellent test design skills and API testing experience
- Experience with UI test automation frameworks (e.g., Playwright)
- Experience with cloud platforms (AWS, GCP, Azure) and containerization (Kubernetes)
- Strong understanding of continuous delivery
- Demonstrated ability to operate and set direction autonomously
- Experience coaching engineering teams on quality practices
- Strong communication and cross-functional collaboration skills
Bonus qualifications include CI/CD tool configuration, GraphQL knowledge, performance engineering expertise (k6), observability tools (OpenTelemetry/Grafana), financial data domain knowledge, backend/data pipeline testing experience, and relevant technical degree.
