Full Time Full Stack Automation Engineer Jobs, Salary up to SGD 7,000 in TOTAL EBIZ SOLUTIONS PTE. LTD. Central Region (Singapore) - Maukerja

Experience:

• 4–8 years in automation, DevOps, cloud infrastructure, or security platform engineering
• Professional experience delivering and supporting production systems
• Built CI/CD pipelines, cloud infrastructure, workflows, or platform integrations (work or strong portfolio)
• Can deliver assigned work with guidance; escalates design decisions
• Strong experience owning production platforms and integrations end to end
• Several years building and running production CI/CD, cloud infrastructure, or workflow automation (not ad hoc scripts only)
• Experience mentoring engineers and leading technical work over multiple quarters

Technical skills:

• Hands-on with at least one major cloud (AWS, Azure, or GCP). Multi-cloud is a plus.
• Terraform, CloudFormation, Pulumi, or similar — standards, review, and ownership
• Kubernetes or cloud-native runtimes (e.g. Cloud Run, managed container services)
• Built or led pipeline design for GitHub Actions, GitLab CI, ArgoCD, Jenkins, or similar
• REST, GraphQL, gRPC, or WebSockets; API design and integration
• Automation platforms, orchestration, or SOAR playbooks
• Prometheus, Grafana, ELK, cloud monitoring, OpenTelemetry, or similar
• SOAR playbooks, orchestration platforms, or enterprise workflow systems
• Familiar with SIEM, SOAR, and SOC workflow systems, or threat intelligence platforms
• Strong Python, Golang, Node.js, or similar for services and automation; scripting (Bash, PowerShell)
• Message queues and pub/sub (Kafka, RabbitMQ, cloud pub/sub, etc.)
• Cloud warehouses, PostgreSQL, Redis, or similar Logging/tracing/metrics, secure coding, release governance

Desirable Skills (Added Advantage):

• Enterprise SIEM, SOAR, SecOps, or threat intelligence platforms.
• Low-code workflow tools (OutSystems, Mendix, Power Apps, ServiceNow, or similar).
• Full-stack development for operator tools and portals.
• BI dashboards or data visualisation.
• Cloud AI/ML and LLM-based workflows.

Education:

Degree in Computer Science, Computer or Electronics Engineering, Information Technology, or a related discipline.

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