Ironbook AI Hiring! Full Time Cloud Support Engineer (Malaysia Onsite) in Federal Territory - Ricebowl

Company Description Ironbook AI is a builder-led company focused on solving complex enterprise AI challenges in data activation, agentic automation, and autonomous data engineering. The organization operates a dual model, combining product development of AI-native systems, such as an autonomous data migration agent, with a high-impact consulting practice serving leading enterprises across APAC. Teams work directly with modern cloud and data platforms, including AWS, Databricks, Confluent, and MinIO, to deliver scalable AI solutions in production environments. Ironbook AI offers an environment for professionals who want to build meaningful systems, advance the capabilities of AI, and contribute to the future of enterprise technology.

Role Description This is a full-time onsite role based in Malaysia for a Cloud Support Engineer. The role involves providing technical support for cloud-based infrastructures, responding to support tickets, and troubleshooting issues related to performance, availability, and security. The Cloud Support Engineer will collaborate with internal teams and enterprise clients to diagnose problems, implement fixes, and recommend improvements across cloud platforms and data ecosystems. Daily responsibilities include monitoring systems, performing routine maintenance, documenting solutions, and contributing to best practices that enhance reliability and customer satisfaction. The role also requires clear communication with stakeholders and proactive identification of potential risks or service disruptions.

Qualifications

Core Responsibilities

1. Technical Support & Troubleshooting

Diagnose and resolve issues across AWS services, including:

Compute: EC2, Auto Scaling, Elastic Beanstalk, Lambda

Storage: S3, EBS, EFS

Networking: VPC, Route 53, Elastic Load Balancer (ELB), CloudFront

Databases: RDS, DynamoDB, Aurora

Additional responsibilities include:

Investigating performance issues, service outages, and configuration errors

Analyzing logs, metrics, and error messages to identify root causes

2. Incident Management

Respond to customer-reported incidents based on severity levels (P1–P4)

Provide real-time support during production outages

Escalate complex issues to AWS service teams when required

Communicate effectively with customers regarding status, impact, and workarounds

3. Architecture & Best Practices Guidance

Advise customers on:

High availability and fault-tolerant architectures

Scalability and performance optimization

Cost optimization strategies

Security best practices, including IAM, encryption, and least-privilege access

Support customers in aligning workloads with the AWS Well-Architected Framework.

4. Monitoring & Optimization

Utilize AWS monitoring and advisory tools such as:

Amazon CloudWatch (metrics, alarms, logs)

AWS X-Ray

AWS Trusted Advisor

Identify risks related to performance, security, and cost

Recommend proactive improvements and optimizations

5. Automation & Scripting

Write, review, and troubleshoot scripts using Python, Bash, and PowerShell

Use AWS SDKs (e.g., Boto3) for automation

Assist with automating deployments and operational tasks

Troubleshoot CI/CD pipelines using tools such as CodePipeline, GitHub Actions, and Jenkins

6. Documentation & Knowledge Sharing

Create and maintain internal knowledge base articles

Document Root Cause Analyses (RCA) for major incidents

Share learnings and best practices with peers to improve overall support quality

Skills Required

Technical Skills

Strong understanding of AWS core services

Linux and Windows system administration

Networking fundamentals (DNS, TCP/IP, VPNs, firewalls)

Scripting and automation experience

Basic security principles and IAM concepts

Soft Skills

Excellent communication skills with the ability to explain complex issues clearly

Strong customer empathy and professionalism

Ability to work under pressure, especially during critical incidents

Analytical mindset with strong problem-solving capabilities

Typical Day-to-Day Activities

Handle customer support cases through a ticketing system

Participate in live calls to resolve critical production issues

Review logs and metrics to diagnose and troubleshoot problems

Recommend architectural and operational improvements

Collaborate with AWS service teams and internal peers