Job Description

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.