Note: The job is a remote job and is open to candidates in USA. Amplifire is an AI learning platform that delivers personalized instruction at enterprise scale for high-stakes industries. The Site Reliability Engineer will improve the reliability, scalability, performance, observability, and operational efficiency of the company’s cloud-based platform through automation, incident response, infrastructure management, and collaboration with engineering and operations teams.
Responsibilities
- Establish and maintain service-level indicators (SLIs), service-level objectives (SLOs), error budgets, and other measures of system health
- Build and continuously improve monitoring, logging, tracing, dashboards, and alerting that provide actionable visibility into application and infrastructure health
- Analyze system behavior, performance, capacity, and reliability trends to proactively identify risks and improvement opportunities
- Partner with engineering teams to define reliability requirements and improve the availability, scalability, and performance of production systems
- Participate in the on-call rotation and respond to production incidents with urgency and sound technical judgment
- Improve incident detection, triage, escalation, communication, mitigation, and recovery processes
- Lead or contribute to blameless post-incident reviews, root cause analysis, and corrective actions
- Develop and maintain runbooks, recovery procedures, and operational practices that improve service resilience and reduce mean time to detect and restore service
- Identify and eliminate operational toil through automation, self-service tooling, and continuous improvement
- Build and maintain cloud infrastructure using Infrastructure as Code practices and tools such as Terraform or AWS CDK
- Improve CI/CD pipelines, deployment safeguards, rollback capabilities, and progressive delivery practices
- Develop internal tools and automation that improve reliability, resilience, and engineering productivity
- Support scalable, secure, and cost-effective production environments
- Partner with software engineers to embed reliability, operability, and observability throughout the development lifecycle while reducing operational friction and helping teams safely own their services in production
- Help engineering teams diagnose complex production issues across application and infrastructure layers
- Contribute to security, compliance, capacity-planning, cloud cost optimization, and operational standards
- Use AI-assisted tools responsibly to improve troubleshooting, automation, documentation, and operational efficiency while sharing knowledge and continuously improving team practices
Skills
- · 4+ years of experience in Site Reliability Engineering, DevOps, cloud infrastructure, systems engineering, software engineering, or a related production-focused role
- · Demonstrated experience supporting reliable, customer-facing applications in a production cloud environment
- · Hands-on experience designing, deploying, and operating production workloads on AWS
- · Experience building or maintaining Infrastructure as Code, observability solutions, incident response processes, and CI/CD automation
- · Experience identifying and reducing operational toil through automation and continuous improvement
- · Experience participating in on-call rotations, troubleshooting production issues, performing root cause analysis, and implementing preventive improvements
- · Proficiency with at least one scripting or programming language, such as Python, Bash, JavaScript/TypeScript, Go, or Java
- · Working knowledge of Linux systems, networking, DNS, HTTP, load balancing, and common cloud architecture patterns
- · Experience with containers and container-based deployment practices; Docker experience is required, while Kubernetes or similar orchestration experience is beneficial
- · Ability to analyze logs, metrics, traces, and system behavior to troubleshoot issues across application and infrastructure layers
- · Understanding of reliability concepts such as SLIs, SLOs, error budgets, availability, latency, capacity planning, and graceful degradation
- · Familiarity with secure configuration, secrets management, access controls, vulnerability remediation, and other operational security fundamentals
- · Experience using AI-assisted development or operational tools to improve productivity, automation, troubleshooting, documentation, or engineering workflows
- · Ability to critically evaluate AI-generated outputs and apply appropriate validation before production use
- · Interest in adopting emerging tools and practices that improve engineering effectiveness while maintaining operational excellence
- · Strong debugging and systems-thinking skills, including the ability to work through ambiguous, cross-service production issues
- · Ability to communicate clearly during incidents and translate technical findings for engineering and business stakeholders
- · Experience collaborating with software engineering, QA, security, support, and product teams
- · Ability to independently own reliability improvements while seeking input and alignment when appropriate
- · A proactive approach to problem-solving and a willingness to challenge existing practices constructively
Company Overview