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Описание вакансии
Текст:
TL;DR
Staff QE (AI): Defining and implementing the quality strategy for company reference data with an accent on automated validation, golden datasets, API and event-driven testing, and measurable release standards. Focus on detecting data drift, schema changes, matching errors, and lifecycle risks while building scalable test automation and influencing engineering quality practices.
Location: Remote - United States
Base compensation: $148,350–$203,550 USD, with potential equity and benefits.
Company
AlphaSense is an AI-powered market intelligence platform that combines domain-specific AI with business and financial content to support research, decision-making, and workflow automation.
What you will do
- Own the quality strategy for company reference data using quality-by-design and automation-by-default principles.
- Improve coverage for provider-data ingestion, record matching, identifier stability, entity delivery, and change events.
- Define data correctness standards and build golden datasets, labeled samples, automated checks, and precision and recall measurements.
- Establish quality metrics and release standards, using production signals to prioritize risk reduction.
- Build scalable automation across data, API, and event-driven interfaces, selecting appropriate unit, component, API, and end-to-end test layers.
- Anticipate data lifecycle risks, partner with developers on test planning, adopt AI for test design and triage, and coach engineers across teams.
Requirements
- 8+ years of hands-on quality engineering experience, including strategy for complex backend or data platforms.
- Experience designing and automating backend and data-system tests, including API and contract testing, pipeline validation, and event-driven or streaming interfaces such as Kafka.
- Strong programming skills in at least one language, such as Python, Kotlin, Java, TypeScript, JavaScript, or Ruby, with the ability to work in unfamiliar codebases.
- Deep knowledge of unit, API, and end-to-end test design, data correctness at scale, CI/CD, and release quality gates.
- Experience using AI to accelerate engineering and testing, with the ability to set direction independently and influence technical and business stakeholders.
Nice to have
- Experience with data pipelines, data-operations tooling, financial or reference data, or evaluating AI and LLM output.
- Hands-on end-to-end automation experience with Playwright.
- BS or MS in a relevant technical field.
Culture & Benefits
- Opportunity to contribute to a fast-growing company.
- Competitive compensation with potential equity.
- Lunch and recreational benefits.
- Occupational health care.
- Equal-opportunity workplace with reasonable accommodation for qualified employees where required by law.
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