Java AI Engineer - Cloud, LLMs & AI-Driven Backends

Accenture in the Philippines; Philippines; On-site; PHP 720,000 - 1,440,000; Full time

Job summary

Accenture in the Philippines is seeking a hands-on Java engineer to build AI-enabled backend services and scalable cloud-based solutions. You will connect Java platforms, APIs, microservices, data pipelines, and AI model endpoints to deliver production-ready features.

You will work across Product, MLOps, Data Science, and Platform teams, applying secure coding practices and CI/CD, while balancing hands-on coding with architectural thinking to drive reliability and automation in a fast-moving

Qualifications

• 3+ years of full-stack development; 2+ years in lead developer or junior architect roles.
• Strong Java programming skills + experience with AI/ML frameworks and tooling
• Hands-on familiarity with DevOps, CI/CD, and monitoring platforms
• Excellent debugging, problem-solving, and communication abilities
• Ability to balance hands-on coding with architectural thinking

Responsibilities

• Build and maintain Java-based, AI-enabled applications and backend services
• Implement DevOps best practices with CI/CD pipelines, observability, and monitoring tools
• Apply secure coding standards including IAM, encryption, and enterprise security practices
• Contribute to system architecture, design discussions, and technical decision-making
• Work with cross-functional teams to deliver high-quality, production-ready AI features

Skills

Java

AI/ML frameworks

Cloud engineering

Backend services

APIs

Microservices

CI/CD

Observability

Secure coding

Architectural thinking

Problem solving

Communication

DevOps familiarity

Education

Bachelor's degree in Computer Science or Engineering

Tools

Spring Boot

Java EE

Spring Framework

Node.js

Quarkus

Micronaut

Job description

Accenture in the Philippines is seeking a hands-on Java engineer to build AI-enabled backend services and scalable cloud-based solutions. You will connect Java platforms, APIs, microservices, data pipelines, and AI model endpoints to deliver production-ready features.

You will work across Product, MLOps, Data Science, and Platform teams, applying secure coding practices and CI/CD, while balancing hands-on coding with architectural thinking to drive reliability and automation in a fast-moving