This role sits in one of the most critical parts of the platform: determining when records from dozens of disparate sources represent the same real-world entity. Graph design and matching strategy are developed in-house, and you’ll be the engineer who turns those concepts into production-ready capability. You’ll shape implementation details, but this is first and foremost a builder role.
You’ll join a team building technology that supports real-world government mission needs. The platform ingests and analyzes data from a wide range of sources, applies AI-assisted workflows to surface what matters most, and provides transparent, explainable recommendations that analysts can trust. Every match, merge, and relationship you create helps turn fragmented information into insight.
You’ll own the matching build lifecycle end to end: blocking strategies, candidate generation, pairwise scoring, clustering, threshold policy, and the deduplication and known-entity checks that reuse the same engine. You’ll also build the provenance framework that lets every node, edge, and assertion in the graph be traced to the source that asserted it, so matching decisions are auditable and explainable.
This is a fully remote role with occasional travel to DEFCON AI headquarters, customer sites, and partner facilities as needed.