Principal Software Engineer – Platform Engineering

About the role

About AlphaSense:

AlphaSense is the AI platform redefining market intelligence and workflow orchestration, trusted by thousands of leading organizations to drive faster, more confident decisions in business and finance. The platform combines domain-specific AI with a vast content universe of over 500 million premium business documents — including equity research, earnings calls, expert interviews, filings, news, and internal proprietary content. Purpose-built for speed, accuracy, and enterprise-grade security, AlphaSense helps teams extract critical insights, uncover market-moving trends, and automate complex workflows with high-quality outputs. With AI solutions like Generative Search, Generative Grid, and Deep Research, AlphaSense delivers the clarity and depth professionals need to navigate complexity and obtain accurate, real-time information quickly. For more information, visit www.alpha-sense.com. Come join us.

About The Role:

AlphaSense runs a large-scale, Kubernetes-native platform built on a modern microservices architecture, serving the majority of the Fortune 500. We're now moving it into a cell-based architecture, where each cell is an independent deployment of the platform, and the cell count is heading from dozens toward hundreds, including private and isolated clouds.

Platform tooling only takes that so far. The rest of the problem is architectural and it sits in the services: how they're structured, how they're bounded, and what they assume about the environment they run in. This role owns that side of the work.

You'll set the architectural direction for how our services scale horizontally across regions, cells and deployment models, and you'll build it rather than specify it. You'll own the environments configuration management framework to operate environments as a fleet, and the services and libraries to make it work. Where the answer is a re-architecture rather than a patch, you design it and you write it. Much of it lands in code other teams own, so influence matters as much as design.

The scope is deliberately broad: hundreds of services, several languages, and the latitude to go after whichever scalability limit matters most. Our main languages are Java, Python, React and Rust.

We use AI tooling heavily and expect the same from you, along with a view on how the rest of engineering should be using it.

What You'll Do:

- Drive the service-side changes cell architecture needs: re-architecture, shared library, etc.

- Decompose hundreds of microservices into sub-systems with independent lifecycles

- Find and close horizontal scalability gaps across regions, cells and deployment models

- Own the environments application configuration management framework end-to-end

- Own the services and libraries specific to private and isolated cloud deployments

- Design and land changes directly in product services, partnering with the teams that own them

- Set the architecture patterns and reference implementations product teams build against