At Informed K12, we believe that operational excellence in school districts is one of the highest-leverage investments in public education. Our technology builds capacity for administrators and gives time and resources back to teachers by fixing one of the most overlooked problems in education: the slow, fragmented processes and workflows that carry a district's most critical work. We have been expanding our impact since 2012, building the product depth, customer relationships, and operational track record required for this work. For engineering, this is a build phase: we are invested in growing the team and giving senior engineers room to define how AI changes the way software gets built here. Much of K-12 software grows by acquisition and cost-cutting. We grow by deeply understanding district pain and building for the future of K12 operations. This role really focuses on software engineering as the discipline of learning by building, with real customers, with real data, without forcing premature abstractions back into the core platform. Informed K12 builds operational software for U.S. school districts. You will be a part of a small group that builds new product hypotheses alongside our most adventurous customers, validates them with real data, and decides what graduates into the broader platform. You will be a senior IC at the heart of that team. If you have shipped prototypes alongside customers under real ambiguity, retired your own projects on purpose, and have a clear understanding of what it means to use code to learn but carefully consider the cost of maintenance over time, then you are a great fit for this role. Our engineering challenges aren't about scale. They're about domain depth and distilling complexity into elegant primitives that model how districts actually work. School districts are among the most process-dense institutions in the country: every workflow encodes board policy, bargaining agreements, and state law, and every district encodes them differently. The hard problem is finding the primitives underneath 100 apparently-unique processes — deciding what's essential variance and what's cruft and unnecessary complexity, without breaking workflows where a mistake means someone doesn't get paid. If you find that kind of complexity more interesting than another distributed-systems problem, you'll like it here.
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed