Senior/Staff Backend Engineer - Distributed System

• AI computing company: we turn GPU hardware into reliable, high-utilisation AI compute through software, orchestration and full lifecycle operations
• What we offer: enterprise GPU cloud and AI inference, software for data centre owners to run their own GPU clouds, turnkey and sovereign AI data centres, edge computing and GPU financing
• Who we work with: GPU owners, data centre operators, enterprises, OEMs, integrators and financiers across multiple markets
• How we work: fast-moving and high-accountability; we value speed, ambition, clarity, ownership and measurable outcomes

Role Summary

Zettabyte’s mission is to make AI compute ubiquitous, seamless and limitless: a cloud where AI just works, anywhere, anytime.

The Senior/Staff Backend Engineer leads the design and implementation of the high-scale backend services and distributed architectures that orchestrate GPU clusters for AI workloads. The role creates APIs that handle GPU allocation, memory management, compute scheduling and multi-tenant isolation.

It tackles problems such as sharing expensive GPU resources efficiently across users, handling GPU memory constraints for large models, and keeping quality of service when workloads compete for compute.

Reporting Line

Reports to: Co-CTO and CPO, * Developer APIs: design APIs that abstract complex GPU operations into simple developer experiences.

• Scheduling: build scheduling algorithms that maximise GPU utilisation while meeting SLAs.
• Resource management: develop resource management for GPU lifecycle, provisioning, allocation, scheduling and release.
• Usage and billing: create usage tracking and billing systems for GPU-hours, memory usage and compute utilisation.
• Monitoring and recovery: implement GPU-specific metrics, health checks and automatic failure recovery.
• Multi-tenancy: build resource isolation, quota management and fair scheduling.
• Model serving: optimise cold starts and implement efficient model loading strategies.
• Interfaces: expose complex infrastructure through intuitive interfaces with frontend engineers, using AI-assisted coding tools.

Distributed Computing, Systems Engineering, Artificial Intelligence (AI), High Tech Industry, GPU (Graphics Processing Unit), Computer Software, Network Operations Center, Cloud Computing, OEM (Original Equipment Manufacturer), Application Programming Interface (API), * 5+ years of backend engineering experience with distributed systems

• Strong proficiency in Go, Python or similar backend languages
• Experience with resource scheduling, orchestration and API design (REST, GraphQL, gRPC)
• Understanding of hardware constraints and system optimisation
• Linux systems knowledge and containerisation experience (Docker, Kubernetes)
• Comfort working with expensive resources where efficiency directly affects cost
• Excitement about novel problems in AI infrastructure and a start-up mindset, comfortable with ambiguity and rapid iteration

Bonus Qualifications

• GPU or HPC cluster management, or GPU virtualisation and sharing technologies
• Understanding of ML and AI workload patterns and requirements
• Background in performance optimisation for compute-intensive workloads
• Experience with high-value resource allocation, billing or metering systems

What Success Looks Like (First 90 to 180 Days)

• GPU allocation and scheduling services delivered with measurable utilisation gains
• Usage tracking accurate enough to bill customers with confidence
• Multi-tenant isolation and quotas in production
• Senior technical leadership visible in design reviews and mentoring

Why This Role Matters

• High stakes: a single API call can allocate thousands of dollars of compute an hour.
• Customer impact: these optimisations decide whether AI start-ups can afford to train their models.

Working Norms at Zettabyte

• Bias to action: deliver drafts quickly, then iterate on feedback
• Be precise: double-check numbers and facts; sloppy analysis creates downstream cost
• Make it usable: package outputs for decision-making, not data dumps
• Own the process: whoever drives a deliverable manages stakeholders and timelines
• Learn the ecosystem: understand GPUs, cluster operations and the buyer landscape, * Compensation: USD 200,000 to 265,000 a year base salary, plus equity
• Benefits: Medical, dental and vision insurance; 401(k) retirement plan; paid time off and US public holidays; equity
• Work authorisation: Required in the United States, without need for visa sponsorship
• Equal opportunity: Zettabyte is an equal opportunity employer; qualified applicants with arrest or conviction records will be considered in line with the California Fair Chance Act

Interested in This Position?