Staff Software Engineer, Social Graph

Want to help us help others? We’re hiring! GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010. Join us! We are seeking a Staff Software Engineer with deep expertise in graph theory, graph-based systems, and large-scale social graph infrastructure . In this role, you will serve as a technical leader driving the architecture, implementation, and scaling of our social graph platform—powering trust, recommendations, user discovery, and other core product experiences. You will collaborate closely with Data Science, ML, Product, and Infrastructure teams to design graph representations, build ingestion and transformation pipelines, and deploy graph-backed models at massive scale. You will set technical direction for how we leverage connectivity, influence, and reputation signals to improve safety, personalization, and engagement across our ecosystem. This is a hybrid role that requires 3 days per week at the office, and we are therefore only able to consider candidates who are located or willing to relocate to San Francisco, CA. The Role Serve as the technical lead for initiatives related to social graph modeling, storage, retrieval, and computation . Architect and scale graph databases and graph query systems capable of supporting billions of nodes and edges with low-latency performance. Design and ship pipelines for ingesting, cleaning, and transforming social and behavioral data into graph structures. Partner with ML teams to productionize graph-based features , including embeddings, similarity signals, trust metrics, and GNN-powered ranking features. Lead the development of graph-informed recommendation, trust, and safety systems , ensuring models reflect real-world connectivity patterns. Define and implement feature engineering strategies leveraging graph topology (e.g., mutual connections, influence scoring, community structure). Contribute to architecture decisions related to streaming systems (Kafka, Flink, Spark Streaming) and real-time graph updates. Mentor engineers and guide best practices on graph design, distributed systems, feature computation, and ML integration. Collaborate with Product to translate graph capabilities into business-impacting features that drive trust, engagement, and discovery. Ensure reliability, scalability, observability, and data quality in all graph-related systems. You 8+ years of industry experience, including significant experience at senior / staff / principal levels . Demonstrated expertise launching and scaling graph-based applications in production. Deep understanding of graph theory , graph algorithms (e.g., traversal, clustering, centrality), and modern graph data structures. Expert-level experience with graph databases (Neo4j, TigerGraph, JanusGraph, DGL-backed systems, etc.) and efficient graph querying . Proven ability to design high-scale pipelines for ingesting and transforming social or behavioral data. Experience with distributed streaming frameworks (Kafka, Flink, Spark Streaming). Hands-on experience incorporating graph-derived features into recommendation, ranking, trust, or safety models. Familiarity with Graph Neural Networks (GNNs) , graph embeddings, or graph-based ranking systems. Strong product intuition and ability to articulate how graph systems drive business outcomes . Ability to influence architectural direction and mentor teams. Preferred Experience supporting real-time or near-real-time graph updates. Background in large social networks, marketplaces, trust safety, or other graph-heavy domains. Track record of cross-functional technical leadership. Publications, patents, or open-source contributions in graph algorithms, GNNs, o ... (truncated, view full listing at source)