Senior Software Engineer, Backend — Systems & Infrastructure

San Francisco, CA · In Person · Full-Time

About Vizcom

Vizcom is building the future of industrial design.

Our mission is to reshape the design process by streamlining the path from concept to creation, helping designers bring more impactful ideas into the physical world.

Design teams at companies like Nike, GM, New Balance, and Hasbro use Vizcom to move from early concepts and sketches through rendering, visualization, and 3D exploration.

We're a Series B company with more than $51M raised and are continuing to expand our engineering team in San Francisco.

The technical surface area is broad: real-time collaboration, GPU inference at scale, distributed systems, enterprise infrastructure, and a modern TypeScript stack supporting professional design teams every day.

The Role

As a Senior Software Engineer, Backend — Systems & Infrastructure, you'll architect and build the backend systems that keep Vizcom fast, reliable, and scalable as our product and customer base grow.

You'll work across systems including GPU workload orchestration, GraphQL performance, real-time event infrastructure, caching, data integrity, and observability.

This is a high-ownership engineering role. You'll be responsible not only for building systems, but also for understanding how they behave in production, identifying bottlenecks, improving reliability, and helping shape the technical decisions that allow Vizcom to scale.

You'll collaborate closely with frontend, infrastructure, and AI engineers to turn complex technical systems into fast, seamless experiences for designers.

What You'll Do

Design and implement scalable APIs using TypeScript/Node, GraphQL, and Postgres.

Profile and optimize performance across queries, resolvers, I/O, and other critical backend paths.

Build and operate distributed systems, including job queues, streaming infrastructure, caching, and background workers.

Partner with AI engineers to integrate GPU inference pipelines into production user workflows.

Build and improve real-time systems supporting collaborative product experiences.

Strengthen reliability through observability, incident reviews, testing, CI/CD, and deployment improvements.

Design secure systems that maintain appropriate data boundaries across customers and enterprise environments.

Write technical RFCs and contribute to architectural decisions as the platform evolves.

Mentor teammates on backend architecture, testing, reliability, and performance.

The Problems You'll Tackle

You'll work on problems such as:

Distributed GPU inference: Managing queueing, scheduling, and performance across bursty GPU workloads.

Real-time collaboration: Building synchronization systems using technologies such as WebSockets and CRDT-based collaboration.

GraphQL performance: Improving caching, batching, resolver performance, and database access patterns.

Scale and reliability: Identifying bottlenecks and designing systems that continue to perform as usage grows.

Enterprise infrastructure: Supporting secure multi-tenant data boundaries and enterprise integrations including SSO, SAML, and SCIM.

Observability: Making it easier to understand system behavior, identify failures, and resolve production issues quickly.

What Your First 90 Days Could Look Like

Days 1–30: Understand

Learn the architecture, production environment, critical backend systems, performance characteristics, and how our engineering team builds and operates software.

Days 30–60: Ship

Take ownership of and ship a meaningful backend or infrastructure improvement, such as a model queue, caching layer, real-time service, or performance optimization.

Days 60–90: Improve the system

Identify a meaningful architectural, performance, or reliability opportunity and drive it forward. This could include reducing latency on a critical API path, improving observability, or authoring an RFC that shapes how a core system evolves.

The specific problems may change as the product and infrastructure evolve. What matters is that you're able to identify high-leverage opportunities and own them through production.