Java AI Engineer: Scalable Backend & GenAI Solutions

Programmers.io; Phoenix (AZ); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Relocation assistance

Health insurance

401(k) match

Job summary

Programmers.io is seeking a senior Java backend engineer to design and build scalable microservices using Java 17/21, Spring Boot, and Spring Cloud. You will develop REST APIs, event-driven services with Kafka, and implement secure architectures (OAuth2/JWT, RBAC) across distributed systems.

Beyond traditional backend work, the role includes AI/GenAI initiatives, RAG workflows, embeddings, and vector databases, with cloud deployment on AWS/Azure/GCP and robust CI/CD pipelines using Docker and

Qualifications

• Extensive Java backend experience with Spring ecosystem.
• Hands-on with microservices, REST APIs and Kafka.
• Experience deploying in cloud environments (AWS/Azure/GCP) and CI/CD pipelines.

Responsibilities

• Design and develop scalable Java backends and microservices.
• Build RESTful APIs and event-driven services with Kafka.
• Implement security, RBAC, OAuth2/JWT and enterprise standards.
• Develop AI/GenAI solutions and RAG workflows, vector databases, and embeddings.
• Deploy and monitor in cloud environments with CI/CD and container tech.

Skills

Core Java

Java 17/21

Spring Boot

Spring Cloud

Hibernate/JPA

REST APIs

Microservices

Kafka

SQL & NoSQL Databases

AI / GenAI

OpenAI / Azure OpenAI

Prompt Engineering

LangChain / LlamaIndex

Embeddings & Semantic Search

Vector Databases

Cloud & DevOps

Docker

Kubernetes

CI/CD

GitHub Actions / Jenkins

Terraform (Preferred)

Tools

Docker

Kubernetes

GitHub Actions

Jenkins

Terraform

Job description

Programmers.io is seeking a senior Java backend engineer to design and build scalable microservices using Java 17/21, Spring Boot, and Spring Cloud. You will develop REST APIs, event-driven services with Kafka, and implement secure architectures (OAuth2/JWT, RBAC) across distributed systems.

Beyond traditional backend work, the role includes AI/GenAI initiatives, RAG workflows, embeddings, and vector databases, with cloud deployment on AWS/Azure/GCP and robust CI/CD pipelines using Docker and