Java Software Engineer

Atos; Phoenix (AZ); On-site; USD 140,000 - 190,000; Full time

Job summary

Atos seeks a Senior Java & AI Engineer to design, build, and deploy AI-powered software. You will blend Java backend with ML/LLM architectures and collaborate with Data Science to scale Python prototypes into production Java code.

You will implement robust microservices with Spring Boot, manage data pipelines for model training, and optimize architectures for high throughput AI responses using vector databases and modern DevOps practices.

Qualifications

• Strong expertise in Java 17+ with backend service design and security.
• Experience building scalable microservices using Spring Boot/Spring Cloud.
• Hands-on AI/ML integration with LLMs and Generative AI APIs.
• Familiarity with vector databases, data pipelines, and RAG workflows.

Responsibilities

• Backend development of robust, scalable microservices in Java.
• Integrate AI/ML models, LLMs, and Generative AI APIs into apps.
• Design data pipelines for model training and inference.
• Create architectures for high throughput and low latency AI responses.
• Implement vector databases for RAG workflows.
• Collaborate with Data Science to productionize Python prototypes into Java.

Skills

Java mastery

Spring Boot

Spring Cloud

Hibernate

Cloud platforms

CI/CD & DevOps

Agile methodologies

Tools

LangChain4j

Spring AI

Deep Java Library (DJL)

Tribuo

Docker

Kubernetes

Job description

We are seeking a skilled Senior Java & AI Engineer. You will design, build, and deploy AI-powered software solutions. You will blend traditional backend Java development with cutting-edge artificial intelligence, machine learning (ML), and Large Language Model (LLM) architectures.

Responsibilities

• Backend Development: Build robust, scalable, and secure backend microservices using Java and Spring Boot.
• AI Integration: Integrate AI/ML models, LLMs, and Generative AI APIs into existing Java applications.
• Pipeline Engineering: Design and maintain data pipelines for machine learning model training and inference.
• Architecture Design: Create system architectures optimized for high throughput and low-latency AI responses.
• Database Management: Implement vector databases for retrieval-augmented generation (RAG) workflows.
• Collaboration: Partner with Data Science teams to operationalize and scale Python-based prototypes into production Java code.

Required Skills and Qualifications

• Core Language: Mastery of Java (version 17 or higher preferred).
• Frameworks: Extensive experience with Spring Boot, Spring Cloud, and Hibernate.
• AI/ML Tools: Hands‑on experience with Java AI frameworks like LangChain4j, Spring AI, Deep Java Library (DJL), or Tribuo.
• Cloud & DevOps: Proficiency in one of AWS, Azure, or GCP, alongside Docker and Kubernetes.
• Strong understanding of software design patterns, CI/CD pipelines, and agile methodologies.