Staff Backend Software Engineer

As a Staff Backend Software Engineer, you will step in as the primary technical owner of the backend architecture. This is a fully hands-on individual-contributor position leading system design, database modeling, and infrastructure decisions from zero to one. Rather than maintaining an existing backend service or delivering features inside a pre-built framework, you will design the foundation connecting agentic AI and computer vision pipelines to distributed business systems, real-time collaboration engines, and multi-tenant structures.

• Demonstrated track record of designing, building, and delivering backend systems from zero to one. \n

• Deep technical expertise in API design, database modeling, and complex schema architecture beyond standard CRUD applications. \n

• Strong hands-on experience architecting distributed systems with complex asynchronous workflows and queue-based processing. \n

• 6 to 14 years of backend software engineering experience, with strong evidence of expanding architectural scope and autonomy. \n

• Hands-on experience with modern infrastructure-as-code tooling (such as Pulumi, Terraform, AWS CDK, or CloudFormation). \n

• Early-stage or venture-backed startup experience strongly preferred; must demonstrate genuine comfort working autonomously in a lean (~20-person) environment. \n

• Located in the United States with standard working-hour overlap with the US East Coast. \n

• Experience with technologies such as TypeScript, Python, Go, Kafka, Postgres, Temporal, AWS, or Pulumi is an asset. \n

• Exposure to multi-tenant architectures, real-time collaborative document software, or 3D/spatial data structures is a plus. \n

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• Own backend architecture end to end and drive foundational technical design decisions across the entire platform. \n

• Design robust APIs, data schemas, and object models supporting complex 3D spatial and interior design data. \n

• Architect and implement distributed systems featuring complex asynchronous workflows, queue systems, eventing, and data-processing pipelines. \n

• Build and optimize systems for real-time collaborative editing and document revision history. \n

• Design and scale secure, multi-tenant backend architecture. \n

• Interface agentic AI and computer vision models with core transactional services and data stores. \n

• Collaborate closely with executive leadership, frontend engineers, and computer vision specialists on overall product and technical roadmap. \n

• Implement infrastructure-as-code and establish backend engineering best practices as the organization scales. \n

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