About this role
Lead quality engineering for AlphaSense's FinData portfolio, spanning financial data generation, delivery, and AI-driven user experiences. Architect quality standards and define testing strategies for data pipelines, AI model validation, and agentic search in an AI-first operating model.
Must have
Fluency with AI tools and proven track record accelerating software delivery
Deep knowledge in at least one of Kotlin, Python, JavaScript, or Java
Proficiency in testing methodologies and deep QA domain knowledge
Experience with Test Management Systems such as Allure TestOps
Excellent test design skills and experience in API testing
Experience with UI test automation frameworks such as Playwright
Experience with cloud platforms AWS, GCP, or Azure and containerization with Kubernetes
Strong understanding of continuous delivery
Ability to operate and set direction autonomously without dedicated QE team
Experience coaching engineering teams on quality-by-design and shift-left practices
Strong communication skills and ability to collaborate across multiple portfolios
Technologies
Responsibilities
Define and drive long-term testing strategy and quality culture for AI Platform
Define quality metrics and coverage standards partnering with product and engineering
Grow test coverage through scalable domain-specific automation and maintain complex test datasets
Guide and support test planning for new features across unit integration and E2E layers
Continuously improve and streamline testing processes and perform targeted exploratory testing
Coach and mentor engineers on sustainable scalable quality practices
Serve as strategic partner to ensure delivery standards through rigorous release gates
Benefits
Recruitment process
Role is part of QE org leading quality on FinData portfolio
Work spans financial data generation delivery and user-facing experiences across multiple teams
Focus on architecting quality standards for AI-centric ecosystem
Emphasis on Quality by Design and Automation by Default principles
Bonus for CI/CD pipeline setup, GraphQL knowledge, performance engineering with k6
Bonus for financial data domain knowledge and backend data pipeline testing experience
BS/MS degree in Computer Science Engineering or Information Technology preferred
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