Cohere
Senior
Lead architecture for Cohere's Model Serving platform running LLMs at scale
This is a senior/lead infrastructure role on Cohere's Model Serving team, setting architecture and technical direction for serving Cohere's LLMs via low-latency, high-throughput, high-availability API endpoints on Kubernetes and GPUs across multiple clouds. Expect deep distributed systems, Kubernetes/GPU, and multi-cloud cost/ops questions plus technical leadership scope.
Step into this interview
Free · a live voice mock calibrated to this exact role
What this interview tests
- Distributed systems architecture on Kubernetes with GPU workloads
- Multi-cloud and hybrid/on-prem serving strategy (GCP/Azure/AWS/OCI)
- Accelerator (GPU/TPU) performance characteristics for latency/throughput
- Org-level compute/storage/network cost and optimization ownership
- Technical leadership: setting standards, senior-level code review, mentoring
- Customer-facing technical leadership for custom deployments
Common question themes
Design a low-latency, high-throughput LLM serving system on Kubernetes with GPU workloads
How do you decide between multi-cloud vs on-prem for a large-scale inference deployment
Explain how you'd optimize throughput given accelerator compute characteristics
Walk through how you've owned infra cost management and driven savings at an org level
Tell me about setting engineering standards and reviewing senior engineers' designs
How would you lead a customized deployment for an enterprise customer with unique requirements
Related interviews
Cohere
Mid
Forward Deployed Engineer, Agentic Platform
Cohere
Mid
Member of Technical Staff, Applied ML
Cohere
Senior
Data Engineer, Data Foundations
Netflix
Senior
Senior Software Engineer, Distributed Systems Engineer 5 - Studio Infrastructure
Senior
Senior Software Engineer, Compute Platform
Staff