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Key Responsibilities and Required Skills for Infrastructure Reliability Engineer

💰 $120,000 - $200,000

EngineeringSite ReliabilityDevOpsCloud Infrastructure

🎯 Role Definition

We are seeking an Infrastructure Reliability Engineer (also known as Site Reliability Engineer or SRE) to own and improve the reliability, performance, and scalability of our cloud-native infrastructure. This role blends software engineering and systems operations to automate infrastructure, design resilient architectures, lead incident response, and continuously measure and improve availability against SLAs and SLOs. The ideal candidate has hands-on experience with Kubernetes, Terraform, observability stacks, CI/CD pipelines, and proven experience driving operational excellence in production environments.

📈 Career Progression

Typical Career Path

Entry Point From:

  • DevOps Engineer transitioning to reliability-focused responsibilities
  • Systems Administrator or Platform Engineer with cloud and automation experience
  • Backend Software Engineer who has worked closely with production deployments

Advancement To:

  • Senior Site Reliability Engineer / Lead SRE
  • Platform Engineering Manager / Head of SRE
  • Principal Reliability Engineer or Architect focused on resiliency and distributed systems

Lateral Moves:

  • Cloud Infrastructure Engineer
  • Platform Engineer (Kubernetes/PlatformOps)
  • DevOps Engineer specializing in CI/CD or security

Core Responsibilities

Primary Functions

  • Design, implement, and maintain scalable and highly available cloud infrastructure using Infrastructure as Code (IaC) such as Terraform, Pulumi, or CloudFormation; ensure reproducible, auditable environments and versioned infrastructure changes.
  • Architect and operate container orchestration platforms (Kubernetes, EKS, GKE, AKS), including cluster lifecycle management, upgrades, autoscaling, networking, and workload scheduling to meet performance and cost objectives.
  • Build and maintain robust CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, ArgoCD) to automate build, test, and deployment processes with a focus on repeatability, security, and zero-downtime deployments.
  • Develop and own service-level objectives (SLOs), service-level indicators (SLIs), and service-level agreements (SLAs); translate business requirements into measurable reliability targets and drive engineering work to achieve them.
  • Lead incident response as an incident commander or subject matter expert: detect incidents, manage communication, triage root cause, lead postmortems, and implement corrective and preventive actions to avoid recurrence.
  • Implement comprehensive observability and monitoring frameworks (Prometheus, Grafana, Datadog, New Relic, OpenTelemetry) to surface system health, latency, error budgets, and capacity planning metrics.
  • Automate routine operational tasks, runbooks, and remediation flows with scripts and tooling (Python, Go, Bash, Ansible) to reduce toil and improve mean time to recovery (MTTR).
  • Design and execute capacity planning, performance testing, and load testing strategies to ensure services scale to meet expected user growth and traffic patterns while optimizing cost.
  • Harden infrastructure security and compliance by integrating security controls, IAM best practices, network segmentation, secret management (Vault, AWS Secrets Manager), and automated policy checks into CI/CD and IaC workflows.
  • Implement blue/green and canary deployment strategies, feature flags, and rollback mechanisms to reduce deployment risk and accelerate safe delivery of new features.
  • Troubleshoot complex distributed systems issues across networking, storage, compute, and application layers; collaborate with developers to isolate and remediate production problems.
  • Maintain and evolve platform tooling for templating, developer self-service (internal dev portals), and standardized deployment environments to accelerate developer productivity and consistency.
  • Create and maintain runbooks, run-time playbooks, and on-call procedures; mentor and train on-call engineers and cross-functional teams on operational best practices and incident handling.
  • Provide end-to-end root cause analysis and actionable postmortems; own tracking and verification of remediation items and measure impact of reliability improvements over time.
  • Integrate and manage logging pipelines (ELK/EFK, Fluentd, Loki) and tracing systems (Jaeger, Zipkin, OpenTelemetry) to provide full-stack observability and rapid diagnostics.
  • Drive cost-optimization initiatives across cloud services, identifying idle resources, rightsizing instances, and implementing cost-aware autoscaling and scheduling.
  • Collaborate with product and engineering stakeholders to ensure new features are designed with reliability, observability, and operability in mind using reliability-focused design reviews.
  • Maintain highly available networking and security infrastructure, including load balancers, ingress controllers, DNS, service mesh (Istio/Linkerd), and DDoS protection in multi-region and hybrid-cloud environments.
  • Champion resiliency engineering practices such as chaos engineering, fault injection, and automated resilience tests to proactively discover and remediate failure modes.
  • Build and extend platform APIs and developer-facing tooling using REST/gRPC and infrastructure orchestration tools to enable self-service and reduce manual operational work.
  • Manage backup, disaster recovery, and business continuity plans including regular testing, recovery time objectives (RTO) and recovery point objectives (RPO) validation.
  • Evaluate and onboard third-party SaaS/PaaS tools while managing operational integrations and vendor relationships to improve platform capabilities and reduce operational burden.
  • Contribute to architecture and roadmap planning for the infrastructure platform to align investments in automation, observability, and tooling with business growth.
  • Monitor, report, and continuously improve reliability KPIs, including uptime, MTTR, and error budgets; present metrics and trends to engineering leadership and stakeholders.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis.
  • Contribute to the organization's data strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within the data engineering team.
  • Assist in onboarding new engineering teams to the platform and provide platform walkthroughs and documentation.
  • Contribute to internal knowledge bases, technical blogs, and runbook libraries to raise team-wide competency.
  • Support cross-functional initiatives related to compliance audits, security reviews, and third-party risk assessments.
  • Participate in call rotations and provide after-hours on-call support as needed, with documented escalation procedures and handoffs.

Required Skills & Competencies

Hard Skills (Technical)

  • Infrastructure as Code (Terraform, CloudFormation, Pulumi) — authoring, testing, and modularizing reusable IaC modules.
  • Kubernetes platform operation and tooling (kubectl, kubeadm, Helm, Kustomize, Operators) and deep familiarity with cluster networking, RBAC, and storage.
  • Cloud provider expertise (AWS, GCP, Azure) including compute, networking, IAM, auto-scaling, and managed services.
  • Observability and monitoring stacks (Prometheus, Grafana, Datadog, OpenTelemetry, ELK/EFK) for building dashboards, alerts, and SLI-based monitoring.
  • CI/CD and GitOps workflows (Jenkins, GitLab CI, GitHub Actions, ArgoCD) and deployment automation for continuous delivery.
  • Scripting and programming (Python, Go, Bash) to build automation, custom tooling, and operational runbooks.
  • Configuration management and orchestration tools (Ansible, Chef, Puppet) and experience integrating them into pipelines.
  • Networking fundamentals (TCP/IP, BGP, load balancing, DNS, service mesh) and troubleshooting distributed networking issues.
  • Security and identity management (IAM, vaults, encryption in transit/at-rest, secrets management) and vulnerability remediation workflows.
  • Incident management and chaos engineering tools and practices (fault injection, Gremlin) to test and validate resilience.
  • Logging and distributed tracing (Fluentd, Logstash, Loki, Jaeger) for root cause analysis and performance optimization.
  • Performance testing and benchmarking tools (k6, JMeter, Locust) and capacity planning techniques.
  • Container image management and CI/CD security scanning (Harbor, ECR, Clair, Trivy) and best practices for secure image pipelines.
  • Cost management and optimization across cloud environments using tagging, rightsizing, and billing analysis tools.

(These technical skills reflect common, in-demand requirements for Infrastructure Reliability Engineers and are optimized for ATS/LLM matching.)

Soft Skills

  • Strong incident leadership and calm decision-making under pressure with excellent verbal and written communication for incident rollups and postmortems.
  • Collaborative partner across engineering, product, and security teams to prioritize reliability work with business impact.
  • Analytical problem solving with a bias for data-driven decision making and measurable outcomes.
  • Proactive mindset to identify toil and engineer long-term automation solutions rather than temporary fixes.
  • Mentorship and knowledge-sharing orientation to upskill teammates on best practices and platform usage.
  • Time management and prioritization to balance reactive incident work with strategic reliability projects.
  • Customer and stakeholder empathy to align operational priorities with user experience and business risk.
  • Continuous learning and adaptability to rapidly evolving cloud-native technologies and operational paradigms.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.

Preferred Education:

  • Master's degree in Computer Science, Cloud Engineering, or related technical field or advanced certifications (e.g., AWS Certified DevOps Engineer, GCP Professional Cloud DevOps Engineer, Certified Kubernetes Administrator).

Relevant Fields of Study:

  • Computer Science
  • Systems Engineering / Software Engineering
  • Information Technology / Cloud Computing

Experience Requirements

Typical Experience Range:

  • 3–8+ years in infrastructure, DevOps, platform engineering, or site reliability engineering roles with progressive responsibility in production systems.

Preferred:

  • 5+ years of hands‑on experience operating cloud-native infrastructure (Kubernetes, Terraform) at scale, leading incident response, and owning platform availability metrics. Experience in multi-region deployments, high-traffic web services, and building developer self-service platforms is highly desirable.
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