Senior Software Engineer

• 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

• 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