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TL API Engineer

Roles & Responsibilities

  • 7+ years of Java experience with several years of Python as a secondary language
  • Hands-on experience building microservices and managing the full end-to-end API lifecycle
  • Experience delivering REST APIs and implementing event-driven integrations (Kafka, RabbitMQ, GraphQL, AWS SQS)
  • MuleSoft experience (API development, integrations, or connectivity) with automation or advanced MuleSoft design patterns

Requirements:

  • 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 to accelerate development and reduce cycle time
  • Apply responsible AI practices, including data privacy, governance, and model evaluation, and design agentic integrations and AI-powered automations

Job description

IF YOU ARE

  • Bringing 7+ years of Java experience and 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

AND YOU WANT TO

  • 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

TOGETHER WE WILL

  • Modernize enterprise integrations using microservices and event-driven architectures

  • Accelerate delivery through AI-assisted development and intelligent automation

  • Improve scalability, reliability, and maintainability of integration services

  • Enable responsible and effective use of AI in integration engineering

  • Build a future-ready integration platform that supports evolving business needs


Our Recruitment Process:

  • CV Screening: Applications are reviewed within 24 hours.
  • Pre-Screening Interview: A brief Q&A session designed to learn more about your experience related to the required job position.
  1. Automated Session (Recommended) – You can complete this session on your own at a time that is convenient for you. The questions and follow-ups are well-structured and designed to highlight your experience and provide detailed insights into your background. This option is recommended because its usually more detailed and allows us to provide feedback from the hiring manager faster.
  2. Session with a Recruiter – You can also have the session with a recruiter. The questions are the same, but the discussion may be a bit less detailed, and feedback might take a little longer.
  • Shortlisting: Qualified candidates are presented to the hiring manager for review.
  • Formal Interviews: Online discussions with the hiring manager or project team, with feedback provided within 1-2 weeks.
  • Offer and Onboarding: Successful candidates receive a formal offer and begin a structured onboarding process.

Information about the processing of your personal data is provided in our Privacy Policy, which is available online a Privacy Policy

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