• Design and validate reliability across our hybrid infrastructure, on-prem data centers and AWS, spanning compute, storage, networking, and serverless technologies, balancing redundancy and headroom against infrastructure cost.

• Drive reliability for our core data infrastructure, including high-throughput streaming and messaging systems, distributed data stores, big-data platforms, and enterprise storage systems, so these hold up under real-time, high-volume load.

• Partner with teams on infrastructure-as-code (Terraform) and platform maturity, container orchestration (Kubernetes), and GitOps workflows, and automate repetitive operational work across deployment pipelines, canary releases, and rollback procedures.

• Define and maintain SLIs and SLOs, and strengthen observability across the stack using tools like Datadog, including alerting, dashboards, structured logging, and distributed tracing, so engineers have the signal they need to understand production state before, during, and after incidents.

• Lead the incident postmortem process to drive systemic fixes, and champion proactive failure testing, fault and latency injection, chaos experiments, and game days that expose weaknesses before production does.

What You'll Bring

• 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, a history of convincing application and infrastructure teams to make difficult reliability-driven changes through technical credibility, clear data, and collaborative problem-solving rather than mandates.

• Mentorship track record: you've actively coached SREs at every level, including seniors, run structured learning initiatives, and can point to engineers whose reliability skills grew materially under your guidance.

• 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: you can identify the hot path and prescribe targeted fixes, whether that's asynchronous I/O, smarter caching, reduced allocations, query rewriting, or connection-pool tuning, and know when the fix belongs in the code versus the infrastructure.

• 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, you study how systems fail and maintain mental (or written) 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: you've defined them, defended them in engineering conversations, and used budget burn rates to drive prioritization decisions.

• Proficiency with infrastructure-as-code (Terraform or similar) and container orchestration (Kubernetes), and a clear-eyed understanding of how infrastructure changes introduce reliability risk.

• Solid networking fundamentals: TCP/IP, DNS, TLS, load balancing, CDN behavior, and how these layers contribute to reliability problems in distributed systems.

• Experience with chaos engineering and failure injection: you've designed and run game days, not just read about them.

• Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.
  
  
  
  In support of pay transparency and equity, the minimum and maximum full-time annual base salary for this role is $175,000 - $225,000 the time of posting, with the potential of an incentive or bonus. While this is our reasonable expectation this is not a guarantee of compensation or salary, actual compensation is influenced by a wide range of factors including but not limited to skill set, level of experience, education, certifications, responsibility, and geographic location. Candidates hired to work in other locations will be subject to the pay range associated with that location. We offer a variety of benefits, including medical, dental, vision, disability insurance, 401(k), EAP, parental leave, unlimited vacation, and company-paid holidays. The specific programs and options available will vary depending on the state, start date, and employment type. Our Talent Acquisition team will be happy to answer any questions you may have. #LI-DN1#LI-Hybrid

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