Staff Site Reliability Operations Engineer

Calix

1d•$136,000 - $265,700•Remote

About The Position

The Calix platform enables Communication Service Providers (CSPs) of all sizes to transform and future-proof their businesses. Through real-time data, automation, and actionable insights delivered via Calix One — our cloud-first, AI-powered platform — CSPs can simplify operations, collapse cost, and accelerate innovation. Calix One brings together the automation of everything and the experience of one, empowering customers to deliver differentiated subscriber experiences while driving acquisition, loyalty, and revenue growth. This is the Calix mission: to enable CSPs of all sizes to simplify, innovate, and grow, strengthening both their businesses and the communities they serve. We’re at the forefront of a once in a generational change in the broadband industry. Join us as we innovate, help our customers reach their potential, and connect underserved communities with unrivaled digital experiences. Role Overview We are seeking a Staff Site Reliability Engineer (SRE) to lead our global platform reliability and drive our next-generation observability strategy on Google Cloud Platform (GCP). In this role, you will leverage Grafana Labs' complete telemetry stack and AIOps methodologies to build intelligent, self-healing infrastructure. You will bring deep expertise in scaling enterprise-grade Google Kubernetes Engine (GKE) topologies, managing high-throughput Kafka event streams, and maintaining high-performance PostgreSQL, AlloyDB, and BigQuery ecosystems at massive scale. Crucially, you will provide deep technical leadership across the entire networking stack, diagnosing complex issues from physical-layer transport up to application-layer protocols. This position is 100% fully remote. You can work from anywhere in the United States or Canada with a reliable internet connection, collaborating with a distributed engineering organization across multiple time zones.

Requirements

Proven track record of high autonomy and successful delivery in a 100% remote engineering environment.
8+ years in SRE, Production Engineering, or Distributed Systems infrastructure roles.
Deep technical knowledge and debugging mastery across all OSI layers, including: L1-L3: Physical/fiber infrastructure awareness, switching, and advanced routing protocols (BGP, OSPF). L4: Transport layer tuning (TCP congestion control algorithms, UDP, QUIC). L5-L7: Session management, TLS termination, DNS architecture, and advanced application protocols (HTTP/3, gRPC).
Expert-level mastery of Google Kubernetes Engine (GKE) internals, custom controllers, multi-cluster networking, and GitOps workflows.
Proven track record managing high-throughput Apache Kafka pipelines and large-scale data environments across PostgreSQL, AlloyDB, and BigQuery.
Deep, hands-on experience deploying and managing Grafana Enterprise/Cloud, Prometheus/Mimir, Loki, and Tempo at scale.
Track record applying AI/ML techniques for time-series anomaly detection, log clustering, and correlation (e.g., Grafana Adaptive Metrics, BigPanda).
Advanced, production-scale expertise utilizing HashiCorp Terraform exclusively to provision and manage multi-region GCP cloud architectures.
High proficiency in Go and Python for building custom infrastructure tooling, Kubernetes operators, and data integration scripts.

Nice To Haves

Exceptional written and verbal communication skills, with an emphasis on creating clear documentation for asynchronous alignment.
Deep knowledge of Google Cloud architectural best practices, Cloud SDN, Cloud Armor, Interconnect, Identity and Access Management (IAM), and cost optimization.
Deep understanding of Linux internals, eBPF-based monitoring, kernel-level networking, and packet analysis tools (Wireshark, tcpdump).

Responsibilities

Architect, optimize, and troubleshoot complex networking infrastructure spanning Layer 1 through Layer 7, ensuring low-latency data transport, secure edge routing, and seamless service mesh integration.
Design, scale, and optimize our unified observability platform using the Grafana Labs suite (Grafana, Mimir, Loki, Tempo, and Beyla).
Deploy machine learning models and automated anomaly detection to cut through telemetry noise, reduce alert fatigue, and predict network or data pipeline bottlenecks.
Drive the architecture, scaling, security, and networking of production Google Kubernetes Engine (GKE) clusters.
Tune, and maintain high-throughput Apache Kafka clusters to guarantee low-latency event delivery and high availability.
Ensure the performance, scalability, and disaster recovery readiness of our transactional and analytical data tiers across PostgreSQL, AlloyDB, and BigQuery.
Integrate AIOps insights with Grafana workflows to automate triage, accelerate root-cause analysis, and trigger auto-remediation scripts.
Champion the long-term technical roadmap for distributed infrastructure engineering and GCP cloud-native observability standards.
Coach senior and junior engineers on advanced debugging techniques, distributed systems thinking, and intelligent operations across a distributed workforce.