Design, build, automate, scale, and operate large-scale production OpenStack clouds. Responsibilities include OpenStack service architecture, Nova compute tuning, Neutron/SDN integrations, Ceph storage performance tuning, HA control plane design, multi-region replication, and automation using Ansible and Terraform. Troubleshoot messaging, hypervisor, and storage layers and support bare-metal-to-cloud deployments.
This is a remote position.
About the Role
We are seeking a deeply technical Senior OpenStack Engineer to design, build, automate, scale, and operate large-scale production OpenStack environments powering enterprise private clouds, MSP platforms, and high-performance digital twin lab infrastructures.
This is not a UI-driven admin role. We are looking for engineers who understand OpenStack at the service, database, messaging, hypervisor, and packet-flow layers — individuals who can troubleshoot RabbitMQ queues, debug Neutron agents, tune Ceph latency, and automate full cloud deployments from bare metal upward.
You will work on multi-region architectures, high-availability designs, NVMe storage fabrics, SDN integrations, and hybrid cloud platforms supporting global customers.
Primary Responsibilities
1. OpenStack Architecture & Platform Engineering
- Design production-grade OpenStack environments across controller, compute, and storage nodes.
- Architect HA control planes using HAProxy, Keepalived, Galera, and RabbitMQ clustering.
- Build scalable cell-based Nova architectures.
- Implement multi-region replication strategies.
- Perform platform capacity modeling and growth forecasting.
2. Compute Virtualization (Nova)
- Nova scheduler tuning and filters.
- CPU pinning and isolation.
- NUMA topology alignment.
- HugePages configuration.
- Live migrations and evacuations.
- GPU passthrough and SR-IOV provisioning.
Hypervisor stack includes KVM, QEMU, Libvirt, and VirtIO.
3. Networking & SDN (Neutron)
- ML2 plugin architecture.
- OVS, OVN, Linux Bridge deployments.
- VXLAN, Geneve, VLAN overlays.
- DVR and L3 routing.
- Floating IP NAT design.
- SR-IOV and DPDK acceleration.
- Integration with BGP EVPN, MPLS, VRFs, and SD-WAN.
4. Storage Engineering
Ceph (Primary Requirement)
- RBD block storage.
- CephFS and RGW object storage.
- CRUSH map tuning.
- Placement group optimization.
- BlueStore performance tuning.
- NVMe and SSD tiering.
Additional exposure to Linstor, DRBD, iSCSI, and NVMe-oF preferred.
5. Image & Lifecycle Services
- Glance image pipelines.
- QCOW2 optimization.
- Cloud-init automation.
- Golden image lifecycle management.
6. Identity & Access (Keystone)
- RBAC modeling.
- LDAP/AD integration.
- SAML/SSO federation.
- Token lifecycle management.
We are seeking a deeply technical Senior OpenStack Engineer to design, build, automate, scale, and operate large-scale production OpenStack environments powering enterprise private clouds, MSP platforms, and high-performance digital twin lab infrastructures.
This is not a UI-driven admin role. We are looking for engineers who understand OpenStack at the service, database, messaging, hypervisor, and packet-flow layers — individuals who can troubleshoot RabbitMQ queues, debug Neutron agents, tune Ceph latency, and automate full cloud deployments from bare metal upward.
You will work on multi-region architectures, high-availability designs, NVMe storage fabrics, SDN integrations, and hybrid cloud platforms supporting global customers.
Primary Responsibilities
1. OpenStack Architecture & Platform Engineering
- Design production-grade OpenStack environments across controller, compute, and storage nodes.
- Architect HA control planes using HAProxy, Keepalived, Galera, and RabbitMQ clustering.
- Build scalable cell-based Nova architectures.
- Implement multi-region replication strategies.
- Perform platform capacity modeling and growth forecasting.
2. Compute Virtualization (Nova)
- Nova scheduler tuning and filters.
- CPU pinning and isolation.
- NUMA topology alignment.
- HugePages configuration.
- Live migrations and evacuations.
- GPU passthrough and SR-IOV provisioning.
Hypervisor stack includes KVM, QEMU, Libvirt, and VirtIO.
3. Networking & SDN (Neutron)
- ML2 plugin architecture.
- OVS, OVN, Linux Bridge deployments.
- VXLAN, Geneve, VLAN overlays.
- DVR and L3 routing.
- Floating IP NAT design.
- SR-IOV and DPDK acceleration.
- Integration with BGP EVPN, MPLS, VRFs, and SD-WAN.
4. Storage Engineering
Ceph (Primary Requirement)
- RBD block storage.
- CephFS and RGW object storage.
- CRUSH map tuning.
- Placement group optimization.
- BlueStore performance tuning.
- NVMe and SSD tiering.
Additional exposure to Linstor, DRBD, iSCSI, and NVMe-oF preferred.
5. Image & Lifecycle Services
- Glance image pipelines.
- QCOW2 optimization.
- Cloud-init automation.
- Golden image lifecycle management.
6. Identity & Access (Keystone)
- RBAC modeling.
- LDAP/AD integration.
- SAML/SSO federation.
- Token lifecycle management.
7. Orchestration & Automation
- Heat orchestration templates.
- Terraform automation.
- Ansible playbooks.
- Heat orchestration templates.
- Terraform automation.
- Ansible playbooks.
Similar Jobs
.png)
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Own and grow enterprise payment partnerships by sourcing, negotiating, and closing integrations with software platforms. Drive go-to-market execution with Sales and Account teams, develop API expertise, collaborate cross-functionally, and track partner performance and business outcomes tied to GPV, seller acquisition, and enterprise wins.
Top Skills:
AfterpayAPIsCash App PayErpIsvSquare Payments Api
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Lead GTM strategy and operations for Global Sales: design segmentation, territory and coverage models, build data-driven investment cases, analyze funnel performance, own WBR/MBR cadence and dashboards, run cross-functional projects from PRD to launch, and champion AI and automation to increase sales productivity.
Top Skills:
LookerSalesforceSnowflake
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Lead a team building evaluation infrastructure and benchmarks for agentic and generative AI. Design automated tests, validate RAG and knowledge grounding, benchmark LLMs, optimize model selection, and translate evaluation results into product and risk recommendations while collaborating cross-functionally and growing an AI-native engineering team.
Top Skills:
AnthropicBleuCmdbsG-EvalGoogle (Llms)Hybrid SearchKnowledge GraphsLlm-As-A-JudgeNumpyOpenaiPandasPythonRetrieval-Augmented Generation (Rag)RougeSemantic Re-RankingSQL
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
