Cadre Inc
Senior Full Stack Engineer (Frontend-leaning)
Cadre Inc, San Francisco, California, United States, 94199
The Frontend-Leaning Role
You'll own major product surfaces in Vizcom’s real-time design environment — from our canvas rendering engine to collaborative UX systems. You'll work across React, WebGL, and GraphQL, shaping performance, interaction design, and developer experience. You'll partner closely with designers, AI engineers, and backend leads to make Vizcom’s interface both beautiful and blazingly fast.
What You’ll Do
Design and implement scalable APIs
in TypeScript/Node with GraphQL and Postgres
Profile and optimize slow paths
— queries, resolvers, and I/O
Build and operate distributed systems : job queues, streaming, caching, and observability
Collaborate with AI engineers
to integrate GPU inference pipelines into user workflows
Improve reliability : lead incident reviews, strengthen CI/CD and deployment flows
Mentor teammates
on backend architecture, testing, and performance thinking
90-Day Outcomes
Ship one critical backend feature (e.g., model queue, caching layer, or realtime service)
Reduce p95 latency in one major API path by ~30%
Author one technical RFC proposing an improvement to architecture or reliability
Implement or document one observability improvement (metrics, traces, alerts)
The Problems You’ll Tackle
Distributed GPU inference and queueing with bursty workloads
Realtime synchronization with WebSocket and CRDT-based collaboration
GraphQL performance: caching, batching, resolver optimization
Secure multi-tenant data boundaries and enterprise integrations (SSO/SAML/SCIM)
What Great Looks Like
5–8+ years building production web systems (TypeScript/Node or similar)
Strength in databases, performance tuning, and distributed systems
Experience operating Kubernetes or similar orchestration environments
Fluency with observability tools and debugging live systems
Bonus : GPU workloads, background job systems, or realtime architectures
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What You’ll Do
Design and implement scalable APIs
in TypeScript/Node with GraphQL and Postgres
Profile and optimize slow paths
— queries, resolvers, and I/O
Build and operate distributed systems : job queues, streaming, caching, and observability
Collaborate with AI engineers
to integrate GPU inference pipelines into user workflows
Improve reliability : lead incident reviews, strengthen CI/CD and deployment flows
Mentor teammates
on backend architecture, testing, and performance thinking
90-Day Outcomes
Ship one critical backend feature (e.g., model queue, caching layer, or realtime service)
Reduce p95 latency in one major API path by ~30%
Author one technical RFC proposing an improvement to architecture or reliability
Implement or document one observability improvement (metrics, traces, alerts)
The Problems You’ll Tackle
Distributed GPU inference and queueing with bursty workloads
Realtime synchronization with WebSocket and CRDT-based collaboration
GraphQL performance: caching, batching, resolver optimization
Secure multi-tenant data boundaries and enterprise integrations (SSO/SAML/SCIM)
What Great Looks Like
5–8+ years building production web systems (TypeScript/Node or similar)
Strength in databases, performance tuning, and distributed systems
Experience operating Kubernetes or similar orchestration environments
Fluency with observability tools and debugging live systems
Bonus : GPU workloads, background job systems, or realtime architectures
#J-18808-Ljbffr