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AIDA RecruitmentPosted 1 month ago

Team Lead API Engineer

RemoteIndia

Full TimeSenior LevelSmall

Job Summary

Design, build, and maintain integration services and microservices using Java or Python, focusing on scalable REST APIs and event-driven integrations with Kafka, RabbitMQ, GraphQL, and AWS SQS. Leverage AI-assisted coding tools like Cursor, Windsurf, and Amp to accelerate development, while evaluating emerging technologies for agentic integrations and responsible AI practices. Modernize enterprise integrations within cloud and CI/CD environments, applying advanced MuleSoft design patterns to improve scalability and reliability. Participate in the recruitment process including CV screening, pre-screening interviews, and formal discussions with the hiring manager.

Required Qualifications

  • 7+ years of Java experience
  • Several years of Python as a secondary language
  • Understanding microservices architecture with hands-on experience building microservices and managing the full end-to-end API lifecycle
  • Delivering REST APIs and implementing event-driven integrations (Kafka, RabbitMQ, GraphQL, AWS SQS)
  • Working with event-driven architecture and asynchronous processing
  • Possessing MuleSoft experience (API development, integrations, or connectivity)
  • Applying MuleSoft automation or advanced MuleSoft design patterns
  • Using AI-assisted coding tools (Cursor, Windsurf, Amp)
  • Practicing responsible AI, including data privacy and governance
  • Learning and adapting quickly to new AI and integration technologies
  • Exploring agentic integrations / AI automation
  • Leveraging open-source integration frameworks and emerging AI productivity tools
  • Operating in cloud & CI/CD environments (AWS preferred)
  • Having GraphQL exposure with the ability to learn and build as needed
  • Design, build, and maintain integration services and microservices using Java or Python, plus relevant open-source frameworks
  • Develop scalable APIs and event-driven integrations with Kafka, RabbitMQ, GraphQL, AWS SQS, etc.
  • Leverage AI-assisted coding tools (e.g., Cursor, Windsurf, Amp) to accelerate development and reduce cycle time
  • Evaluate and adopt emerging AI tools to improve developer productivity, code quality, and operational efficiency
  • Design and implement agentic integrations and AI-powered automations that enhance business processes
  • Apply responsible AI practices, including data privacy, governance, and model evaluation
  • Work with event-driven architectures and asynchronous processing in production

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