Staff Engineer, QE
AlphaSense
Unknown, Unknown
Full-Time
Competitive
OfficeSenior
The worlds most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients own research content.
The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us!
As we transition into an AI-First Operating Model and move from exploration into execution at scale, we are seeking a Staff Quality Engineer to join our AI Platform team and serve as a strategic catalyst for this shift.
In this high-impact role, you will be accountable for architecting the quality standards that underpin our next generation of market intelligence. Your remit is to define how we build, test, and operate in an AI-centric ecosystem. You will lead quality initiatives that ensure our engineering workflowscovering everything from complex data pipelines and AI model validation to system observability and agentic search interactionsare robust, scalable, and AI-boosted. You will be a key leader in establishing "AI-First" as our standard operating procedure, defining the quality gates that enable us to deliver state-of-the-art market intelligence with confidence and precision at scale.
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