Sr. Software Engineer – Infrastructure
- Compensation
- Not disclosed
- Location
- NYC, NY
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 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.
Nice to have
- 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.
Full description
STLabs is an AI service management platform that resolves employee requests end-to-end, grounded in a living model of the enterprise. This matters because we're able to resolve requests with full context - the people, systems, services, and policies that define how an organization actually runs. Requests that used to take days of back-and-forth resolve in minutes, right where employees already work.
About the Role
As we scale our SaaS platform to support increasingly complex enterprise environments, our graph-based data architecture is becoming a critical strategic pillar. We’re looking for a Senior Engineer with deep experience building and scaling graph-centric, multi-tenant data systems for large-scale SaaS products.
In this role, you’ll own the evolution of our graph data tier—designing performant, secure, and scalable graph models and storage strategies that enable rich relationships, deep querying, and intelligent insights across tenants.
This is a hands-on, high-impact role where you’ll shape the technical foundation of how we represent, store, traverse, and analyze interconnected enterprise data at scale.
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-tenant graph architecture: tenant boundaries, access control models, resource isolation, and performance fairness.
- Implement tooling for onboarding, migrations, tenant provisioning, graph expansion, and lifecycle management.
- Collaborate across product, infrastructure, and security teams to ensure the graph layer meets enterprise SLAs, security, and compliance requirements.
Technical Leadership
- Establish standards around modeling, relationship semantics, data governance, and observability for graph workloads.