Senior Site Reliability Engineer – Hiring Globally

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🔥 55 minutes ago

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Cognativ

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2018

💼 Consulting

🥽 AR/VR

🤖 Artificial Intelligence

Consulting • AR/VR • Artificial Intelligence

Cognativ is an app development agency based in Melbourne, Australia. They combine user experience design, product strategy, and software engineering to deliver mobile and web applications, e-commerce systems, and branded digital experiences. Their specialties include UX and UI design, website and app development (iOS, Android, React Native, React. js, node. js, Python), conversion optimisation, and emerging technologies such as AI/machine learning and AR/VR; they position themselves as quality-focused IT services and consulting partners.

📋 Description

• ** • - Own service objectives. Define SLIs and SLOs for the services that matter, manage error budgets, and use them to drive prioritization and change-rate decisions. Make reliability a measured number, not a feeling. • - Make observability trustworthy. Own alert quality end-to-end: high signal-to-noise, alarms that reliably catch the incidents they are meant to catch, and the discipline to turn off a misleading alarm until it is fixed properly. Build the dashboards and the custom metrics, exporters, and instrumentation (CloudWatch, OpenTelemetry) needed to see the system clearly. • - Lead incident response. Run incidents calmly, drive mean-time-to-recovery down, and produce blameless postmortems with action items that actually get closed. Improve and own the on-call rotation and its health. • - Plan capacity and performance. Forecast and right-size compute (especially GPU), Kafka/MSK throughput and partitioning, RDS/TimescaleDB load, and Redis. Catch saturation before customers do. • - Own business continuity and disaster recovery. Backups, replication, failover, and recovery for RDS, MSK, Redis, and the edge fleet. Define RPO/RTO and prove them with regular, tested game days, not assumptions. • - Keep the edge fleet healthy. Remote diagnosis and recovery over AWS IoT, container auto-update over systemd timers, and the ongoing CentOS 7 migration to the containerized media stack (Ubuntu 22.04). • - Engineer away toil. Write real software (Python, Golang, Bash) to automate operational work, self-heal common failures, and make reliability repeatable instead of heroic. • - Govern production change safely. Enforce collaborative, reviewed change management; protect the system from risky, unilateral changes (topology, instance-count, scaling, and config). • **

🎯 Requirements

• ** • - AWS certification is mandatory. A current AWS Certified DevOps Engineer – Professional or AWS Certified Solutions Architect – Professional is strongly preferred. • - 10+ years in Site Reliability Engineering or production operations at scale. We do not expect mastery of every area below on day one. We expect real depth in several and the ability to ramp quickly on the rest. • - Demonstrated SLO/error-budget practice. You have defined SLIs and SLOs, run against an error budget, and used it to make real decisions. • - Strong production observability skills. Deep with metrics, logs, alarming, and dashboards (CloudWatch, OpenTelemetry, and/or Prometheus/Grafana/Datadog), and able to build the instrumentation when it does not exist. • - Proven incident command. You have led incidents, owned an on-call rotation, and written postmortems that changed how a system behaved. • - Capacity planning and performance experience across compute, databases, and a messaging or streaming system (Kafka/MSK ideal). • - Disaster recovery ownership: backups, replication, failover, and tested RPO/RTO. • - Software engineering ability for automation. Comfortable writing Python, Golang, and Bash to build reliability tooling, not just configure off-the-shelf tools. • - Expert with Terraform (or equivalent IaC) and strong Linux administration (shell plus Linux GNU utils), comfortable from cloud to bare-metal/edge. • - Database operations experience with PostgreSQL (time-series a plus). • - A reliability mindset: you instrument before you guess, and you write the runbook. • Nice to have • - Operating GPU workloads and serving computer-vision or ML models in production (CUDA, Deep Learning AMIs, inference scaling). • - Apache MSK / Kafka and streaming-data operations (Kinesis, Kinesis Video Streams). • - AWS IoT Core at scale: device provisioning, certificates, secure tunnelling. • - Managing a fleet of edge / on-premise devices (golden images, remote update, systemd). • - Operating and modernizing legacy systems (Java 8, Jetty, CentOS). • - Chaos engineering / game-day practice, and capacity modeling. • - Familiarity with Bazel in a monorepo; Cloudflare, Cognito/Auth0, API Gateway. • **