Requirements:
- Minimum 3 years of professional software engineering experience building and operating production backend systems in an AWS or comparable cloud-native environment.
- A bachelor’s degree in computer science, Software Engineering, or a related field is preferred.
- Equivalent professional experience and demonstrated technical ability are acceptable.
- Strong, hands-on proficiency in Go (Golang) for production backend development.
- Experience with AWS, Kubernetes and Apache Kafka.
- Experience with SQL and NoSQL databases.
- Knowledge of microservices, distributed systems and high-volume transaction processing.
- Demonstrated experience designing, building, and operating services handling thousands of transactions per second, with the ability to explain how throughput and performance were measured.
- Practical experience implementing dynamic scaling and horizontal scaling for production workloads.
- Hands-on experience deploying and operating containerized applications using Kubernetes.
- Practical experience with Apache Kafka, including producers, consumers, topics, partitions, consumer groups, and failure handling.
- Hands-on experience with relational databases (RDBMS) and NoSQL databases, specifically
- Couchbase, including data modelling, querying, indexing, and performance optimization.
- Strong understanding of RESTful APIs, service integration, concurrency, and distributed systems fundamentals.
- Experience with automated testing, version control, code reviews, and CI/CD pipelines.
- Understanding of production monitoring, troubleshooting, performance optimization, and service reliability.
- Strong problem-solving skills, sound technical judgment, and the ability to work independently while collaborating effectively with a team.
- Experience with AWS services such as EKS, EC2, ECS, Lambda, S3, RDS, DynamoDB, SQS, or related services, as relevant to the architecture.
- Experience with Infrastructure as Code using Terraform, AWS CDK, or CloudFormation.
- Familiarity with Docker, Helm, Kubernetes autoscaling, and resource management.
- Experience with observability tools such as Prometheus, Grafana, Open Telemetry, or CloudWatch.
- Understanding of distributed system reliability patterns, including idempotency, backpressure, circuit breakers, rate limiting, and graceful degradation.
- Experience with load testing, capacity planning, latency analysis, and performance profiling.
- Knowledge of cloud security fundamentals, including IAM, least-privilege access, secrets management, encryption, and secure API design.
- Experience optimizing cloud infrastructure for cost and operational efficiency.
Pay: RM10,000.00 - RM120,000.00 per month
Work Location: In person
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