Senior Java Backend Engineer – Ai-Augmented Engineering

INGEPSY; Bogotá ciudad; Presencial; COP 120.000.000 - 180.000.000; Jornada completa

Descripción de la vacante

INGEPSY in Bogotá, Colombia is seeking a Senior Java Backend Engineer to design and build scalable, production-grade enterprise applications as part of a large-scale digital transformation program. You will lead backend development, create robust APIs, and drive cloud-native solutions with AWS, Docker, and Kubernetes while integrating AI-powered tooling to accelerate delivery.

The role requires 7+ years of Java experience, strong Spring Boot and microservices expertise, and collaboration with

Formación

• 7+ years of hands-on experience in Java backend development.
• Strong expertise in Java, Spring Boot, REST APIs, and microservices.
• Experience developing and supporting enterprise-scale backend applications.
• Hands-on experience with AWS, Docker, Kubernetes, and CI/CD pipelines.
• Experience integrating applications with APIs, messaging platforms, or enterprise integration technologies.
• Practical experience using AI-powered software development tools, such as GitHub Copilot, Cursor, Claude Code, or OpenAI Codex.
• Ability to demonstrate how AI tools have been used for code generation, debugging, test creation, refactoring, code reviews, documentation, or developer productivity.
• Strong understanding of software engineering best practices, testing, security, performance, and scalability.

Responsabilidades

• Design, develop, and maintain scalable backend applications using Java, Spring Boot, and microservices architecture.
• Build robust RESTful APIs and backend services supporting enterprise operational workflows.
• Develop cloud-native solutions using AWS, Kubernetes, Docker, and CI/CD pipelines.
• Integrate backend services with enterprise platforms through MuleSoft, Kinesis, messaging systems, and third-party APIs.
• Use AI-powered development tools throughout the SDLC to accelerate coding, debugging, testing, refactoring, code reviews, and technical documentation.
• Apply AI tools thoughtfully to improve engineering productivity while validating generated code for quality, security, performance, and maintainability.
• Collaborate with Product Owners, architects, and business stakeholders to translate requirements into scalable technical solutions.
• Optimize applications for performance, security, scalability, and reliability.
• Develop and maintain unit, integration, and automated tests to support high-quality releases.
• Participate in technical design discussions, code reviews, and continuous improvement initiatives.
• Troubleshoot production issues and contribute to application modernization and digital transformation initiatives.

Conocimientos

Java backend development

Spring Boot

Microservices

REST APIs

Cloud-native development

AI-powered tooling

Herramientas

AWS

Docker

Kubernetes

CI/CD

GitHub Copilot

Cursor

Claude Code

OpenAI Codex

Descripción del empleo

Senior Java Backend Engineer to build scalable, production-grade enterprise applications for a large-scale digital transformation program. This role is strongly focused on Java, Spring Boot, microservices, and cloud-native development, with AI-powered engineering tools integrated into the software development lifecycle. You'll work as a hands-on builder, using tools such as GitHub Copilot, Cursor, Claude Code, and OpenAI Codex to accelerate development, testing, debugging, refactoring, and technical documentation while maintaining high engineering standards.

Your Impact

• Design, develop, and maintain scalable backend applications using Java, Spring Boot, and microservices architecture.
• Build robust RESTful APIs and backend services supporting enterprise operational workflows.
• Develop cloud-native solutions using AWS, Kubernetes, Docker, and CI/CD pipelines.
• Integrate backend services with enterprise platforms through MuleSoft, Kinesis, messaging systems, and third-party APIs.
• Use AI-powered development tools throughout the SDLC to accelerate coding, debugging, testing, refactoring, code reviews, and technical documentation.
• Apply AI tools thoughtfully to improve engineering productivity while validating generated code for quality, security, performance, and maintainability.
• Collaborate with Product Owners, architects, and business stakeholders to translate requirements into scalable technical solutions.
• Optimize applications for performance, security, scalability, and reliability.
• Develop and maintain unit, integration, and automated tests to support high-quality releases.
• Participate in technical design discussions, code reviews, and continuous improvement initiatives.
• Troubleshoot production issues and contribute to application modernization and digital transformation initiatives.

Skills & Experience

Must Have

• 7+ years of hands-on experience in Java backend development.
• Strong expertise in Java, Spring Boot, REST APIs, and microservices.
• Experience developing and supporting enterprise-scale backend applications.
• Hands-on experience with AWS, Docker, Kubernetes, and CI/CD pipelines.
• Experience integrating applications with APIs, messaging platforms, or enterprise integration technologies.
• Practical experience using AI-powered software development tools, such as GitHub Copilot, Cursor, Claude Code, or OpenAI Codex.
• Ability to demonstrate how AI tools have been used for code generation, debugging, test creation, refactoring, code reviews, documentation, or developer productivity.
• Strong understanding of software engineering best practices, testing, security, performance, and scalability.
• Strong troubleshooting and problem-solving skills.
• Excellent written and verbal communication and collaboration skills.

Set Yourself Apart With

• Experience with MuleSoft, Amazon Kinesis, Kafka, or other messaging/event-driven platforms.
• Experience integrating with complex enterprise or third-party vendor systems.
• Experience using AI agents or LLM-powered tools beyond basic code completion.
• Exposure to AI-assisted application modernization or large-scale engineering transformation.
• Experience with cloud-native architecture and distributed systems.
• Experience supporting production systems in high-volume or mission-critical environments.