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Ebpf Linux Jobs in San Ramon, CA (NOW HIRING)

Walmart

(USA) Principal, Software Engineer

Fremont, CA · On-site

$143K - $286K/yr

The role requires deep expertise in Ceph, Linux internals, OpenStack, and large-scale ... eBPF, with proven expertise in infrastructure automation using Python, Ansible, and Terraform.

fal

Software Engineer, Site Reliability

San Francisco, CA · On-site

$67.25 - $89.25/hr

... of Linux networking, container networking (CNI plugins, VXLAN, BGP), and DNS • Experience ... eBPF, XDP) • Experience with security tooling (Falco, Coroot, SIEM) • Experience with bare ...

Walmart

(USA) Principal, Software Engineer

Hayward, CA · On-site

$143K - $286K/yr

The role requires deep expertise in Ceph, Linux internals, OpenStack, and large-scale ... eBPF, with proven expertise in infrastructure automation using Python, Ansible, and Terraform.

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Ebpf Linux information

See San Ramon, CA salary details

$40

$61

$79

How much do ebpf linux jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for ebpf linux in San Ramon, CA is $61.82, according to ZipRecruiter salary data. Most workers in this role earn between $56.15 and $66.35 per hour, depending on experience, location, and employer.

What is an eBPF Linux engineer?

An eBPF Linux engineer is a software professional who specializes in working with eBPF (extended Berkeley Packet Filter) technology on the Linux operating system. eBPF allows for the execution of sandboxed programs in the Linux kernel, enabling advanced networking, security, and observability features without modifying kernel source code. Engineers in this role typically develop, optimize, and troubleshoot eBPF programs for use cases such as network monitoring, performance analysis, and security enforcement. They need a strong understanding of Linux internals, networking, and programming in C and sometimes Rust or Go. eBPF Linux engineers are increasingly in demand due to the growing use of cloud-native and containerized environments.

What are the key skills and qualifications needed to thrive as an eBPF Linux engineer?

To thrive as an eBPF Linux Engineer, you need strong skills in Linux systems programming, networking fundamentals, and proficiency with C or Go, often supported by a computer science degree or equivalent experience. Familiarity with eBPF tools (like bpftrace, libbpf, or bpftool), kernel debugging, and knowledge of containerization platforms are typically required. Analytical thinking, problem-solving, and effective collaboration set top professionals apart in this field. These competencies are crucial for developing efficient, secure, and scalable system observability or networking solutions within complex Linux environments.

What are some common challenges faced when developing with eBPF on Linux systems?

Developing with eBPF on Linux often involves navigating kernel version compatibility, as eBPF features evolve rapidly and may not be available on older kernels. Debugging eBPF programs can also be challenging due to strict verifier constraints and limited debugging tools. Additionally, integrating eBPF with existing monitoring or networking solutions requires a solid understanding of both kernel space and user space interactions. Collaborating with platform engineers and security teams is common, as eBPF programs frequently impact system performance and security.

What is the difference between Ebpf Linux vs Linux Kernel Developer?

AspectEbpf LinuxLinux Kernel Developer
Required credentialsKnowledge of eBPF, Linux internals, C programmingDeep understanding of Linux kernel, C, and kernel modules
Work environmentDeveloping and deploying eBPF programs within Linux systemsWriting, maintaining, and optimizing Linux kernel code
Employer and industry usageTech companies, cloud providers, security firms using eBPF for monitoring and securityOperating system vendors, enterprise IT, open-source projects

Ebpf Linux specialists focus on developing eBPF programs to enhance Linux system capabilities, while Linux Kernel Developers work on core kernel code. Both roles require strong C skills and Linux knowledge but differ in scope and focus.

What job categories do people searching Ebpf Linux jobs in San Ramon, CA look for?

The top searched job categories for Ebpf Linux jobs in San Ramon, CA are:

What cities near San Ramon, CA are hiring for Ebpf Linux jobs?

Cities near San Ramon, CA with the most Ebpf Linux job openings:

Ebpf Linux jobs near you
Infographic showing various Ebpf Linux job openings in San Ramon, CA as of June 2026, with employment types broken down into 35% Full Time, 46% Part Time, and 19% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,584 per year, or $61.8 per hour.

Software Engineer - Cloud Infrastructure

FriendliAI Corp

San Francisco, CA • On-site

$203K - $241K/yr

Full-time

Medical

Posted 24 days ago

Job description

About the job
FriendliAI is looking for a Cloud Infrastructure Engineer to own the architecture and evolution of the cluster platform behind our GPU-accelerated AI inference cloud. As a Software Engineer, Cloud Infrastructure, you will design how our clusters are built and connected, extend Kubernetes where its defaults fall short, and own the network path that inference traffic depends on.
Inference is an unforgiving workload for Kubernetes. Traffic is bursty and latency-sensitive, GPU capacity is scarce and inelastic, tenants must stay isolated, and multi-node serving depends on the network holding up under sustained load. This is a hands-on architecture role for an engineer who has already run large clusters in production and wants to push them further.
Key Responsibilities
Cluster Architecture
  • Own the architecture of our multi-cluster, multi-tenant Kubernetes fleet across both managed and self-managed clusters: cluster topology, control plane and etcd lifecycle, and zero-downtime upgrades.
  • Extend Kubernetes with custom controllers, operators, and CRDs so platform behavior is encoded in software rather than runbooks.
  • Design GPU scheduling and capacity strategy, including topology-aware placement, node pools, priority and preemption, and quota across tenants.
  • Build autoscaling that matches inference traffic: queue-driven pod scaling, node autoscaling, scale-to-zero, and cold-start reduction.

Networking
  • Own the Kubernetes network data plane: CNI, IPAM, DNS, ingress, and L4/L7 load balancing.
  • Design cross-AZ, cross-region, and cross-cluster connectivity, and operate the service mesh for routing, mTLS, and traffic policy.
  • Debug production network issues (packet loss, conntrack exhaustion, MTU mismatches, DNS latency, load balancer behavior) and drive permanent fixes.

Reliability & Collaboration
  • Define SLOs for platform-critical systems and lead post-incident hardening.
  • Deliver infrastructure as code with Terraform, Helm, and GitOps.
  • Partner with the inference engine, platform, SRE, and security teams to turn serving requirements into platform capabilities.

Qualifications
  • 5+ years designing, building, and operating large-scale Kubernetes infrastructure in production.
  • Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
  • Proven experience operating large-scale, high-traffic network services in production.
  • Deep understanding of Kubernetes internals: API server, scheduler, controller loops, kubelet, and etcd.
  • Strong command of Kubernetes and cloud networking: CNI, kube-proxy/eBPF datapaths, DNS, load balancing, service mesh, and VPC routing.
  • Proficiency with AWS, Terraform, Helm, and Ansible.
  • Programming skills in Go or Python, with the ability to build infrastructure tooling and automation.
  • Strong debugging skills across distributed systems, containers, and the Linux networking stack.
  • Clear written and verbal communication, including the ability to document architectural decisions for other engineers.

Preferred Experience
  • Large-scale Kubernetes operations in a high-traffic domain such as gaming, e-commerce, or public cloud.
  • Cilium and eBPF, including kube-proxy replacement or upstream contributions.
  • Cluster provisioning and lifecycle management with Kubespray or similar Ansible-based tooling.
  • GPU orchestration: NVIDIA GPU Operator, device plugins, or Dynamic Resource Allocation (DRA).
  • High-performance networking for distributed workloads: RDMA/RoCE, InfiniBand, EFA, SR-IOV, or NCCL tuning.
  • Multi-cloud, hybrid-cloud, or bare-metal Kubernetes operations.
  • Contributions to Kubernetes, Cilium, Istio, or other CNCF projects.

Benefits
  • Flexible working hours
  • Daily lunch and dinner provided; unlimited snacks and beverages
  • Supportive and highly collaborative work environment
  • Health check-up support and top-tier equipment/hardware support
  • A front-row seat to the generative AI infrastructure revolution
  • Competitive compensation, startup equity, health insurance, and other benefits.

About FriendliAI
FriendliAI is the fastest inference cloud for agents, built to run frontier open-weight models in production at scale. It delivers up to 7x faster output token speed, up to 90% lower inference costs, and 99.99% uptime across the most demanding agent workloads - long-context inference, real-time streaming, and accurate tool calling.
We are a small, fast-moving team doing work that matters at one of the most exciting moments in the history of technology. With our world-class inference stack, we are building the platform teams can actually rely on.

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