Sr. Software Engineer – Infrastructure

Responsibilities

• Graph Data Architecture Architect, evolve, and optimize our multi-tenant graph data model, including node/edge schema design, relationship modeling, partitioning, and traversal strategies.
• Define and implement tenancy models for graph storage—balancing shared-graph vs. tenant-isolated subgraphs, hybrid partitioning, or database-per-tenant graph deployments.
• Develop data architecture for graph sharding, indexing, and high-throughput traversal, ensuring low-latency queries even as topology size and complexity scale.
• Backend & Data Layer Engineering
• Build backend services that interact heavily with datastores, including APIs, data-access layers, ingestion workflows, and graph mutation/query pipelines.
• Optimize query performance through indexing improvements, caching of subgraphs, tuned traversal patterns, and distributed graph execution.
• Multi-Tenancy & Platform Scalability
• Own decision-making around multi-tenancy graph architecture: tenant boundaries, access control models, resource isolation, and performance fairness.
• Implement tooling for onboarding, migrations, tenant provisioning, graph expansion, and lifecycle management.
• Collaboration
• Collaborate across product, infrastructure, and security teams to ensure the graph layer meets enterprise SLAs, security, and compliance requirements.

Qualifications

• 5+ years of professional software engineering experience in production SaaS environments.
• Hands-on experience designing, scaling, or operating multi-tenancy databases in production.
• Strong understanding of graph modeling, schema design for nodes/edges, indexing, and query/traversal optimization.
• Proficiency in a modern backend language (Go, Python, Java, Node.js, etc.).
• Solid grounding in distributed systems concepts, partitioning, caching, and performance optimization.
• Experience making architectural decisions in fast-changing, high-scale environments.

Preferred Experience

• Scaling graph-backed SaaS products for enterprise customers with large, complex topologies.
• Familiarity with distributed graph engines, distributed SQL, NoSQL, or horizontally scalable datastores.
• Experience building observability for graph workloads: query heatmaps, traversal metrics, cardinality analysis.
• Prior experience with major re-architecture efforts—e.g., moving from relational to graph, multi-tenant transitions, or large-scale migrations.