Mid/Senior Full Stack Engineer

About the role

Job Title: Mid/Senior Full Stack Engineer Key Skills: Java, Spring Boot, React, REST APIs, Microservices, JavaScript, TypeScript, Python, Bash, CI/CD, Docker, AI-Assisted Development Experience: 3+ YOE Location: San José, Costa Rica Mode: Hybrid – 2–3 days per week on-site

We at Coforge are hiring Mid/Senior Full Stack Engineer (#006fu00000QeELXAA3-9) with the following skill set.

Key Responsibilities

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Design, develop, and own end-to-end features across backend and frontend layers, from technical design and development through deployment and production support.

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Build scalable RESTful APIs and microservices using Java and Spring Boot while contributing to frontend development primarily with React.

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Manage CI/CD pipelines, containerized deployments, production troubleshooting, and operational automation using Python and Bash.

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Leverage AI-assisted development tools such as GitHub Copilot, Cursor, and Claude Code to accelerate coding, testing, debugging, and documentation while ensuring code quality and security.

Required Skills & Qualifications

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3+ years of professional software development experience.

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Strong Java programming skills and understanding of object-oriented design principles.

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Hands-on experience developing microservices using Spring Boot.

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Experience designing and integrating RESTful APIs and working with relational or NoSQL databases such as PostgreSQL, MySQL, or MongoDB.

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Frontend development experience with React or comparable modern frameworks, including JavaScript/TypeScript, HTML, and CSS.

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Experience with unit and integration testing using tools such as JUnit, Mockito, or Jest.

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Hands-on experience with CI/CD pipelines, Docker, and tools such as Jenkins, GitHub Actions, or GitLab CI.

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Proficiency in Python and Bash scripting for automation and operational troubleshooting.

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Strong production debugging skills, including monitoring and logging, and proficiency with Git-based collaborative workflows.

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Hands-on experience with AI coding assistants and LLM tools, with the ability to review and validate AI-generated code for correctness, security, and maintainability.

Preferred Skills:

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Experience with Go and its ecosystem.

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Exposure to Kubernetes and cloud platforms such as AWS, GCP, or Azure.

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Experience with system design, scalability, and performance optimization.

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Knowledge of observability tools such as Prometheus, Grafana, Splunk, or OpenTelemetry.

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Experience building AI-powered features or integrating LLM APIs, including RAG, AI agents, or MCP.