{"id":3756351,"url":"https://alion.io/job/zus-coffee-regional-devops-engineer","title":"Regional DevOps Engineer","company":{"id":3012167,"name":"ZUS Coffee","domain":"zuscoffee.com","url":"https://alion.io/company/zuscoffee","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon ECS","optional":false},{"name":"AWS","optional":false},{"name":"AWS Fargate","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Grafana","optional":false},{"name":"Node JS","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Terraform","optional":false},{"name":"AWS Lambda","optional":true},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-11-04T15:23:22Z","employer_posted_date":null,"last_verified_at":"2026-11-04T15:23:22Z","board_verified":false,"closed_at":null,"days_open":2,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":2},"description":"Position Responsibilities\n\nWe are looking for a DevOps Engineer to own the reliability, availability, and operational health of our production platform — the AWS infrastructure and Go and Node.js microservices that our customers and stores depend on every day.\n\nThis is not a \"keep the servers running\" role. This is a reliability ownership role responsible for how our services are deployed, observed, scaled, and recovered across multiple regions.You will be the person who makes production predictable — defining what \"healthy\" means through SLOs, building the systems that detect problems before customers do, and eliminating the classes of incidents that keep coming back.\n\nWhat You Will Own\n\nProduction reliability and availability of services across multiple regions: uptime, latency, and performance under high traffic\n\nService Level Objectives (SLOs), Service Level Indicators (SLIs), and error budgets — defining them, tracking them, and using them to drive engineering decisions\n\nIncident response and root cause analysis (RCA) for production issues, including blameless postmortems and the preventive actions that follow\n\nAWS infrastructure for containerised services: ECS, Application Load Balancers, Auto Scaling, CloudWatch, and VPC networking\n\nCI/CD pipelines for microservices — deployment reliability, infrastructure consistency, and the reduction of manual intervention\n\nInfrastructure as Code (Terraform / CloudFormation) and the automation of recurring operational tasks\n\nObservability across the platform: metrics, logging, distributed tracing, dashboards, and alerting\n\nService resilience patterns in partnership with development teams: health checks, circuit breakers, retry strategies, fault tolerance, redundancy, and graceful degradation\n\nOperational runbooks and on-call response processes\n\nRequired Technical Skills\n\nExtensive hands-on experience managing production workloads on AWS\n\nHands-on expertise with AWS ECS (Fargate and EC2 launch types) and Docker containerisation\n\nProficiency in VPC configuration, Application Load Balancers (ALB), and Network Load Balancers (NLB)\n\nExperience managing Auto Scaling to sustain high-traffic production environments\n\nProven ability to support and optimise distributed microservices written in Go and Node.js\n\nExperience automating infrastructure with Terraform or CloudFormation\n\nSkilled in building internal tools and automation scripts using Go, Python, and Bash\n\nHands-on experience building and maintaining CI/CD pipelines for microservices\n\nStrong working knowledge of observability tooling: Prometheus / Grafana, AWS CloudWatch, and OpenTelemetry\n\nPractical understanding of SLOs, SLIs, error budgets, and resilience patterns (circuit breakers, retries, health checks, graceful degradation)\n\nRequired Engineering Collaboration Skills\n\nAbility to work with development teams to improve service architecture — influencing how services are built, not just how they are deployed\n\nComfort leading incident response under pressure and communicating clearly to both engineers and non-technical stakeholders\n\nAbility to run blameless postmortems that produce real preventive actions, not just a document\n\nStrong written communication — runbooks, RCAs, and infrastructure decisions should be legible to the next engineer on call\n\nSelf-directed: able to spot reliability risks, prioritise them, and drive fixes without being told where to look.\n\nRequirements\n Experience Requirements\n\n4–7+ years of experience in Site Reliability Engineering, DevOps, or Production Engineering\n\nDemonstrated experience supporting a distributed microservices architecture in production\n\nExperience operating high-traffic production systems — and owning what happens when they fail\n\nExperience participating in on-call rotations and leading incidents through to resolution and RCA\n\nNice to Have\n\nExperience managing multi-region infrastructure\n\nExperience operating high-scale microservices systems\n\nKnowledge of service mesh architectures\n\nExperience with AWS ECR, Lambda, or event-driven architecture\n\nExperience with AWS cost optimisation\n\nBackground in F&B, retail, or operational-heavy consumer businesses with peak-hour traffic patterns\n\nSkills\nDevOps, Docker 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