Sr. Software Engineer, Materials and Purchasing

Higharc•Remote, Remote

8h•Remote

About The Position

Higharc is seeking a pragmatic Senior Software Engineer to build our new Materials & Purchasing vertical — connecting the homes people design in Higharc to the products they actually buy in the world. This is a founding role on a new team. Materials & Purchasing brings product catalogs into the Higharc platform, enriches the home data model, and ties design decisions to real-world availability, pricing, and procurement. You'll partner closely with the Showroom and Estimates teams to bring materials catalogs through the platform, and you'll design the rule engines that manage pricing, inventory, availability, and the constraints that govern how selections come together. You'll move fast by building on what's already proven while carving out what's new. You don't need to be an architect on day one. You do need a high level of ownership, strong UX instincts, and comfort reasoning about complex, interdependent systems.

Requirements

5+ years of full-stack engineering experience building polished, user-facing features
Professional competency with React, SQL, API design, and query optimization
Experience with configurator, customization, or rule-engine UX
A track record building extensible production systems
Strong UX intuition and an ability to reason about complex constraint systems
An entrepreneurial spirit and a high tolerance for building something new

Nice To Haves

Familiarity with 3D/CAD or visual-design-tool ecosystems
Experience with catalogs, procurement, e-commerce, or materials/pricing data

Responsibilities

Build and maintain full-stack features spanning UI, API layer, business logic, and data models
Design and implement rule engines that manage pricing, inventory, availability, and selection constraints
Enrich the home data model to connect design decisions to the products bought in the real world
Architect extensible, maintainable systems that scale as this new vertical grows
Build configuration and selection experiences where users navigate many interdependent choices
Optimize backend performance including query tuning, N+1 resolution, indexing strategies, and scaling bottlenecks
Build complex search, filtering, and querying systems across large catalog datasets