Staff Platform Engineer, Core Cloud Platform

The world’s 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! The Core Cloud Platform team is responsible for AlphaSense’s entire cloud infrastructure, including AWS account management, networking, storage and kubernetes clusters. We build the underlying Platform that supports hundreds of services and is used by over 400 globally distributed Engineers.

This is a Staff Engineer role with real breadth. It requires both operational and software development skills, the ability to lead projects and the need to collaborate with Engineering leaders and very senior Engineers across dozens of teams. You will be instrumental in setting the architectural roadmap for our Cloud Platform, ensuring the scalability and performance align with AlphaSense's rapid growth. We're looking for someone who genuinely embraces AI tooling in their day-to-day work, appreciates the productivity value it brings, and is motivated to make our infrastructure ever-more AI friendly