Senior Software Engineer

AM53 Smart Solutions

. Develop, maintain, and enhance backend applications, APIs, integrations, consumers, jobs, and critical transactional workflows .

Posted 10/16/2026full-timeRemote • BrazilSeniorWebsite

Tech Stack

Tools & technologies

ApacheAWSAzureCassandraCloudDockerGoogle Cloud PlatformGrafanaJavaJenkinsKafkaKotlinKubernetesLinuxMongoDBMySQLOraclePostgresRabbitMQSparkSplunkSpringSpring BootSpringBoot

About the role

Key responsibilities & impact

Develop, maintain, and enhance backend applications, APIs, integrations, consumers, jobs, and critical transactional workflows
Design and implement secure, resilient, scalable, observable, and high-performance solutions
Participate in architecture discussions, technical refinements, standards definition, and technology evolution strategies
Contribute to system modernization by promoting software engineering best practices and reducing technical debt
Provide production support, troubleshooting, incident analysis, root cause identification, and vulnerability remediation
Conduct code reviews and mentor less experienced professionals, fostering the team’s technical excellence
Develop and enhance CI/CD pipelines, automations, and processes that increase delivery productivity and quality

Requirements

What you’ll need

Experience developing with Java and Spring Boot
Experience with Git and version control workflows
Experience developing REST and RESTful APIs
Experience with distributed architectures and microservices
Knowledge of messaging and queues (Kafka, RabbitMQ, SQS, or similar technologies)
Experience with containers (Docker) and orchestration platforms (Kubernetes)
Knowledge of CI/CD tools (Jenkins, GitHub Actions, or similar technologies)
Experience with relational databases (Oracle, MySQL, PostgreSQL) and non-relational databases (MongoDB, Cassandra, or similar technologies)
Experience with unit, integration, and automated testing
Experience with observability and monitoring tools (New Relic, Dynatrace, Grafana, Splunk, or similar technologies)
Experience developing and troubleshooting in Linux environments
Knowledge of SOLID principles, design patterns, Clean Architecture, and DDD
Knowledge of resilient, scalable, event-driven architectures
Knowledge of TDD and BDD
Experience documenting APIs using Swagger/OpenAPI
Knowledge of Spring Cloud
Knowledge of Kotlin
Knowledge of Apache Spark
Experience with AWS (S3, ECS, EKS, SQS, EMR, Lambda, and other related services)
Knowledge of Azure or GCP
Knowledge of the fundamental concepts of Generative AI and Large Language Models (LLMs)
Experience integrating applications with AI APIs and language model-based services
Knowledge of prompt engineering, context management, and AI development tools such as GitHub Copilot, Kiro, or similar technologies