Back End Developer

Kloudius Services; Kuala Lumpur; On-site; MYR 120,000 - 240,000; Full time

Job summary

Kloudius Services is seeking a skilled Backend Software Engineer to design, develop, deploy, and operate scalable backend services on AWS. You will build reliable systems using Go, Kubernetes, Kafka, and relational/NoSQL databases.

You will work on production systems that handle high throughput, scale with demand, and maintain performance under load, taking ownership from design through production and delivering maintainable, well-tested software.

Qualifications

• 3+ years designing and operating production backend systems on AWS or similar cloud
• Proficient in Go (Golang) for production backend development
• Experience with scalable, high-throughput services
• Experience deploying containerized apps with Kubernetes
• Experience with Apache Kafka and databases (SQL/NoSQL)

Responsibilities

• Design, develop, and maintain backend services and APIs using Go.
• Build scalable, distributed, event-driven systems handling thousands of transactions per second.
• Design interfaces, data flows, and integration patterns for independent deployment and scaling.
• Apply sound software design principles and architecture patterns.
• Identify performance bottlenecks and optimize resource usage.
• Develop on AWS, implement autoscaling and IaC.
• Write tests and participate in code reviews.

Skills

Go (Golang)

Kubernetes

Apache Kafka

Couchbase

SQL/NoSQL databases

Tools

AWS

Golang

Docker

CI/CD

Job description

We are seeking a skilled Backend Software Engineer to design, develop, deploy, and operate scalable backend services on Amazon Web Services (AWS). The successful candidate will build reliable, high-performance systems using Go (Golang), Kubernetes, Kafka, and relational and NoSQL databases.

This role requires practical experience developing and operating production systems that handle thousands of transactions per second, scale dynamically in response to changing workloads, and maintain performance and reliability under load.

We are looking for an engineer who combines strong programming fundamentals with sound architectural judgment, takes ownership of their work from design through production, and consistently delivers maintainable, well-tested software.

Key Responsibilities

Backend Development and Architecture

• Design, develop, and maintain backend services and APIs using Go (Golang).
• Build scalable, distributed, and event-driven systems capable of handling thousands of transactions per second.
• Design service interfaces, data flows, and integration patterns that support independent deployment, horizontal scaling, and future growth.
• Apply sound software design principles, appropriate abstractions, and proven architectural patterns without introducing unnecessary complexity.
• Identify and resolve performance bottlenecks, concurrency issues, and resource constraints.

AWS Cloud Infrastructure and Dynamic Scaling

• Develop and deploy production services on AWS using appropriate computer, networking, storage, and managed service offerings.
• Implement horizontally scalable services that dynamically adjust capacity in response to changing traffic and processing demand.
• Deploy and operate containerized workloads using Kubernetes.
• Configure and optimize autoscaling, resource allocation, health checks, and service recovery.
• Apply infrastructure-as-code and automated deployment practices to ensure repeatable, consistent environments.
• Consider performance, availability, security, and cloud operating costs when making engineering decisions.

Event Processing and Data Management

• Build asynchronous, event-driven processing pipelines using Apache Kafka.
• Design reliable message producers and consumers, including appropriate handling of retries, duplicate messages, ordering, and processing failures.
• Design and optimize relational database schemas, SQL queries, indexes, transactions, and data migrations.
• Design, develop, and optimize NoSQL data models using Couchbase, ensuring efficient data access, high throughput, scalability, and performance in distributed systems.
• Understand data consistency, concurrency, transaction boundaries, and the trade-offs between relational and NoSQL storage.
• Ensure data integrity and resilience across distributed services.

Quality, Reliability, and Production Operations

• Write clean, maintainable, well-documented code supported by automated unit, integration, and appropriate end-to-end tests.
• Participate constructively in code reviews, design reviews, and technical discussions.
• Instrument services with meaningful logs, metrics, traces, dashboards, and actionable alerts.
• Troubleshoot production issues through systematic investigation and root-cause analysis.
• Design for failure, including dependency outages, traffic spikes, timeouts, partial failures, and message-processing errors.
• Participate in production support and incident response as appropriate for the team.
• Continuously improve service performance, reliability, security, and maintainability.

Engineering Collaboration and Ownership

• Translate business and product requirements into practical technical designs and deliverable work.
• Own assigned features and services from initial design through implementation, deployment, and ongoing operation.
• Communicate technical decisions, risks, dependencies, and trade-offs clearly.
• Collaborate with other engineers, product stakeholders, and infrastructure teams.
• Contribute to engineering standards and help improve development practices across the team.

Required Qualifications

• Minimum 3 years of professional software engineering experience building and operating production backend systems in an AWS or comparable cloud-native environment.
• Strong, hands‑on proficiency in Go (Golang) for production backend development.
• 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.

Preferred Qualifications

• 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, OpenTelemetry, 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.

Engineering Standards and Expectations

• Ownership: Take responsibility for delivering working software and maintaining its production health, not just completing assigned coding tasks.
• Technical depth: Understand why a solution works, its limitations, and how it behaves under load and failure.
• Quality by design: Treat automated testing, code review, security, and observability as standard parts of development.
• Evidence‑based decisions: Use measurements, benchmarks, logs, and production data to validate assumptions and diagnose problems.
• Pragmatic architecture: Choose solutions that meet current requirements while allowing for sensible future growth; avoid both premature optimization and avoidable technical debt.
• Continuous improvement: Learn from incidents, feedback, code reviews, and new technologies, and turn those lessons into better engineering practices.
• Clear communication: Explain technical decisions and trade‑offs in language appropriate for both technical and non‑technical stakeholders.

Education

• A bachelor’s degree in computer science, Software Engineering, or a related field is preferred. Equivalent professional experience and demonstrated technical ability are acceptable.
• Measures of Success
• Deliver reliable backend features that meet agreed requirements and delivery commitments.
• Build and maintain services that sustain target throughput and latency under representative workloads.
• Demonstrate effective scaling behavior as traffic and processing demand increase.
• Maintain appropriate automated test coverage and production observability.
• Diagnose and resolve issues efficiently, with lasting improvements following significant incidents.
• Produce readable, maintainable code and contribute positively to team engineering standards.
• Make sound technical decisions that balance delivery speed, reliability, maintainability, security, and cost.