Staff Site Reliability Engineer

We're looking for a Staff Site Reliability Engineer to serve as a principal reliability partner and technical authority across our infrastructure and platform teams, setting reliability standards and technical direction for the broader SRE practice. You'll operate across our hybrid infrastructure, on-prem and cloud, and across both the application and infrastructure layers that keep our real-time advertising platform running at scale, proactively surfacing systemic risks and driving meaningful architectural improvements while respecting each team's ownership of their own platforms.

Responsibilities

Influence application and infrastructure teams on the reliability changes that matter most, translating postmortem findings, SLO burn rates, and architectural risk signals into prioritized engineering work; Mentor and develop SREs at every level, providing structured code reviews, pairing on complex reliability investigations, and building practice standards and a career ladder; Help drive Nexxen's AI strategy within the SRE space, exploring and championing AI-powered tooling for proactive reliability and operational efficiency; Drive latency and throughput improvements at the code and infrastructure level, profiling hot paths and producing data-grounded recommendations; Lead architectural reliability reviews and map failure domains, championing circuit breakers, timeouts at every network boundary, queue-based load levelling, and graceful degradation; Design and validate reliability across hybrid infrastructure (on-prem data centers and AWS), balancing redundancy and headroom against cost; Drive reliability for core data infrastructure, including streaming and messaging systems, distributed data stores, big-data platforms, and enterprise storage; Partner on infrastructure-as-code (Terraform), container orchestration (Kubernetes), and GitOps workflows, and automate repetitive operational work across deployment pipelines, canary releases, and rollbacks; Define and maintain SLIs and SLOs, and strengthen observability across the stack using tools like Datadog; Lead the incident postmortem process to drive systemic fixes, and champion proactive failure testing, fault and latency injection, chaos experiments, and game days

Requirements

8+ years of software development and site reliability or production engineering experience, including a track record of leading reliability initiatives across multiple teams and measurably improving reliability, availability, and performance of complex distributed systems at scale; Proven ability to influence without authority, convincing application and infrastructure teams to make difficult reliability-driven changes through technical credibility, clear data, and collaborative problem-solving; Mentorship track record, including coaching SREs at every level, running structured learning initiatives, and developing engineers whose reliability skills grew materially; Strong understanding of observability practices, structured logging, metrics, distributed tracing, and alerting, with hands-on experience with Datadog, Prometheus, Grafana, or equivalent; Code-level performance expertise, including identifying hot paths and prescribing targeted fixes such as asynchronous I/O, smarter caching, reduced allocations, query rewriting, or connection-pool tuning; Experience with AI-assisted observability and agentic workflows (e.g., LLM-based coding and ops copilots, AI-driven runbooks) to accelerate triage and root-cause analysis; Deep hybrid cloud expertise, on-prem infrastructure and AWS, including multi-AZ and multi-region resilience, auto scaling behavior under burst, and failover handling; Hands-on experience with distributed, high-throughput data infrastructure, such as streaming and messaging systems, distributed NoSQL or in-memory data stores, big-data or analytics platforms, and enterprise-grade storage systems; A near-obsessive interest in failure domains, including studying how systems fail and maintaining models of blast radius and cascade paths; Proficiency with Linux internals, network diagnostics (tcpdump, netstat, curl, traceroute), and system-level debugging under production conditions; Solid SLO/SLI/error-budget practice, including defining them, defending them, and using budget burn rates to drive prioritization; Proficiency with infrastructure-as-code (Terraform or similar) and container orchestration (Kubernetes), with an understanding of how infrastructure changes introduce reliability risk; Solid networking fundamentals: TCP/IP, DNS, TLS, load balancing, CDN behavior, and their contribution to reliability problems in distributed systems; Experience with chaos engineering and failure injection, including designing and running game days; Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience

Benefits

Medical; dental; vision; disability insurance; 401(k); EAP; parental leave; unlimited vacation; company-paid holidays; potential incentive or bonus