Our Customer:

A product-focused organization developing innovative enterprise-grade solutions, with a strong emphasis on modern engineering practices, AI-driven development, and high-performance distributed systems.

Your tasks:

• Develop innovative, business-critical applications as a hands-on full-stack expert using Java, Spring, React, and related technologies.
• Own and lead the complete engineering lifecycle, including technical discovery, solution design, architecture, implementation, testing strategy, DevOps, production readiness, and continuous improvement.
• Lead architecture and design decisions for complex services, APIs, front-end capabilities, integration flows, and cloud-ready components.
• Act as a technical authority for Java/Spring, React, microservices, cloud/hybrid, and container-based solutions.
• Translate business needs into scalable, maintainable, secure, and testable technical solutions.
• Guide other developers through remote pairing, code reviews, design reviews, mentoring, and hands-on technical leadership.
• Drive XP practices, including pair programming, TDD/BDD, continuous integration, evolutionary design, and fast feedback loops.
• Design and develop distributed systems with a focus on resilience, service discovery, scalability, observability, and performance.
• Identify modernization opportunities, reduce technical debt, and improve system reliability, observability, performance, and deployment quality.
• Promote engineering excellence through clean code, automation, testability, secure coding, reusable components, and clear technical documentation.
• Work with CI/CD pipelines, automated quality gates, deployment automation, and production-readiness practices.
• Design, develop, and deploy cloud/hybrid solutions in container-based environments such as Kubernetes or Cloud Foundry.
• Use AI-assisted development tools to accelerate coding, unit-test generation, refactoring, documentation, troubleshooting, API exploration, and code-review preparation.
• Apply responsible AI practices in software engineering, including validation of generated output, data sensitivity, security, intellectual property awareness, and human-in-the-loop review.
• Identify practical AI use cases that improve developer productivity, reduce manual effort, and increase delivery quality.
• Evaluate technology options, make architectural trade-offs, and communicate technical recommendations to engineering and management stakeholders.

Required experience and skills:

• 8+ years of hands-on software engineering experience, including significant experience with enterprise-scale systems.
• Expert-level experience with Java, including Spring, Spring Boot, Spring Cloud, microservices, RESTful APIs, and integration-oriented architecture.
• 4+ years of front-end development experience, mainly with React.
• Strong knowledge of modern JavaScript/TypeScript frameworks, component design, state management, and reactive UI patterns.
• Strong experience with distributed systems design, including service resilience, service discovery, circuit breaker patterns, scalability, observability, and performance tuning.
• Strong experience with TDD/BDD and automated testing using JUnit, Jasmine, Mockito, Protractor/Selenium, or equivalent modern tools.
• Hands-on experience with CI/CD, Jenkins or equivalent pipelines, automated quality gates, deployment automation, and production-readiness practices.
• Experience designing, developing, and deploying cloud/hybrid solutions in container-based environments such as Kubernetes or Cloud Foundry.
• Experience with Kotlin, functional programming, Java Streams, and modern JVM ecosystem practices.
• Practical experience using AI-assisted development tools such as GitHub Copilot, ChatGPT/OpenAI-based tools, or equivalent AI engineering assistants.
• Ability to use AI tools for coding, unit-test generation, refactoring, documentation, troubleshooting, API exploration, and code-review preparation.
• Understanding of responsible AI usage in software engineering, including data sensitivity, security, intellectual property awareness, validation of generated output, and human-in-the-loop review.
• Ability to evaluate technology options, make architectural trade-offs, and communicate technical recommendations clearly to engineering and management stakeholders.
• Strong ownership and ability to prioritize complex work, drive decisions, and operate effectively in a rapidly changing environment.
• Excellent problem-solving skills, strong engineering judgment, critical thinking, and ability to simplify complex technical challenges.
• BSc in Software Engineering, BS degree in Computer Science, or equivalent practical engineering experience.

Would be a plus:

• Experience integrating AI/LLM capabilities into applications, workflows, developer tooling, or automation processes.
• Ability to identify practical AI use cases that improve developer productivity, reduce manual effort, and increase delivery quality without compromising security or maintainability.