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Salary: USD 148,350 - 203,550 / annual
AlphaSense is an AI platform for market intelligence and workflow orchestration used by thousands of leading organizations. The Reference Entity Data Services (REDS) team owns the authoritative company data that powers insights across the platform—connecting records from multiple providers into one trusted view and supplying it to search, company profiles, and downstream product teams.
As Staff Quality Engineer for REDS, you will define and build the quality strategy from the ground up, working closely with engineering and product leadership to make quality a measurable, integrated part of how the team ships.
Key responsibilities:
- Own the quality strategy for AlphaSense's company reference data, built on quality-by-design and automation-by-default principles.
- Close test coverage gaps on critical workflows: ingesting provider data, matching records, maintaining identifier stability, and delivering entity data and change events to dependent product teams.
- Define what "correct" means for company data and build golden datasets, labeled samples, and automated checks to prove it—including measuring match precision/recall and false merge/split tradeoffs.
- Set quality measures and release standards the team uses to ship with confidence.
- Build and grow scalable automation across data, API, and event-driven interfaces; determine appropriate test layers (unit, component, API, E2E).
- Anticipate data lifecycle risks (provider drift, schema changes, late/conflicting records) and build regression coverage.
- Partner with developers on test planning for new features so automation is ready as code ships.
- Use production signals to focus effort where it reduces the most customer risk.
- Bring AI into test design, maintenance, and triage.
- Coach engineers and influence across teams to raise the quality bar.
Requirements:
- 8+ years hands-on quality engineering experience, including strategy-setting for complex backend or data platforms.
- Hands-on experience designing and automating tests for backend and data systems: API testing, contract testing, data pipeline validation, event-driven/streaming interfaces (e.g., Kafka).
- Strong programming skills in at least one language (Python, Kotlin/Java, TypeScript/JavaScript, Ruby) and comfort in unfamiliar codebases.
- Deep expertise in test design across unit, API, and end-to-end layers with judgment about appropriate placement.
- Experience validating data correctness at scale, ideally in matching, identity, or pipeline-driven systems.
- Strong grasp of continuous delivery, CI/CD, and release quality gates.
- Track record using AI to speed up engineering and testing.
- Proven ability to set direction independently and influence without authority.
- Clear, confident communication with technical and business stakeholders.
Bonus: data pipeline/data-ops tooling experience, Playwright E2E automation, financial/company/reference data background, AI/LLM output evaluation experience, BS/MS in relevant technical field.
