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AlphaSense is a market intelligence platform trusted by over 6,000 enterprise customers, including a majority of the S&P 500. The company uses AI-driven search and insights across equity research, company filings, event transcripts, and proprietary content to help sophisticated organizations remove uncertainty from decision-making.
This Principal Software Engineer role focuses on platform engineering and owns the architectural evolution of AlphaSense's large-scale, Kubernetes-native microservices platform. The company is transitioning to a cell-based architecture where each cell represents an independent deployment, scaling from dozens to hundreds of cells including private and isolated cloud deployments.
You will drive service-side architectural changes required for this cell-based transition, decomposing hundreds of microservices into sub-systems with independent lifecycles. Key responsibilities include identifying and closing horizontal scalability gaps across regions, cells, and deployment models; owning the environments application configuration management framework end-to-end; designing and implementing changes directly in product services while partnering with owning teams; and setting architectural patterns and reference implementations for product teams to build against.
You'll work across multiple languages (Java, Python, React, Rust) and collaborate with Cloud Platform, SRE, and DevEx teams to define service and platform boundaries. The role emphasizes hands-on architecture work—you design solutions and write code rather than just specify them. You'll also mentor Staff and Senior engineers, raise the architectural bar across the organization, and embed AI tooling into day-to-day development practices.
Ideal candidates have deep experience architecting large microservice estates (hundreds of services), proven track records decomposing service estates into independently-evolving sub-systems, and expertise in horizontal scalability across regions and independent deployments. Strong cloud-native background (Kubernetes, containers, AWS) and experience externalizing configuration from application code are essential. Experience with cell-based, multi-tenant, or multi-region architectures is highly valued.
