Staff QE

AlphaSense

2d•$148,350 - $203,550

About The Position

As AlphaSense transitions into an AI-First Operating Model and moves from exploration into execution at scale, they are seeking a seasoned Senior Quality Engineer to join their QE org and serve as a strategic catalyst for this shift. In this high-impact role, the individual will be accountable for architecting the quality standards that underpin their next generation of market intelligence. The remit is to define how AlphaSense builds, tests, and operates in an AI-centric ecosystem. The role involves leading quality initiatives that ensure 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. The individual will be a key leader in establishing "AI-First" as the standard operating procedure, defining the quality gates that enable the delivery of state-of-the-art market intelligence with confidence and precision at scale.

Requirements

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

Nice To Haves

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

Responsibilities

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.