Java Developer: Spring Boot + AI/RAG Pipelines

BeaconFire Inc; California; Vor Ort; USD 90.000 - 120.000; Vollzeit

Zusammenfassung

BeaconFire Inc. in California is seeking a software engineer to build scalable web applications using Java 8/17, Spring Boot, SQL/NoSQL, and Kafka in a dynamic team.

You will write clean, maintainable code, conduct testing, and own the full development lifecycle in an Agile Scrum setting. You will also implement AI integrations with LangChain4j and Spring AI, staying current on RAG strategies, embeddings, retrieval optimization, and reranking.

Qualifikationen

• Experience with SDLC and Java ecosystem.
• Familiarity with APIs and data structures like Collections, Maps, Lists.
• Knowledge of relational databases and SQL.

Aufgaben

• Develop scalable web apps using Java 8/17, Spring Boot, SQL/NoSQL, and Kafka.
• Write clean, maintainable code with focus on testability.
• Conduct testing to ensure reliability and performance.
• Perform code reviews to enforce quality and best practices.
• Own full SDLC within an Agile Scrum team including planning to release.
• Create technical docs for apps, APIs, and systems.
• Ship APIs and services to production with CI/CD, monitoring, and security.
• Stay up to date with Java tech and related frameworks.
• Implement RAG pipelines using Spring AI and LangChain4j with vector DB.
• Keep current on RAG tooling, embeddings, retrieval, and reranking.

Kenntnisse

Java

Spring Boot

SQL

NoSQL

Kafka

CI/CD

Testing

Agile Scrum

Code reviews

Documentation

Ausbildung

Master’s Degree in Computer Science

0-1 year Java experience

Tools

MySQL

PostgreSQL

React.js

HTML

CSS

Spring AI

LangChain4j

Vector databases

RabbitMQ

Jobbeschreibung

BeaconFire Inc. in California is seeking a software engineer to build scalable web applications using Java 8/17, Spring Boot, SQL/NoSQL, and Kafka in a dynamic team.

You will write clean, maintainable code, conduct testing, and own the full development lifecycle in an Agile Scrum setting. You will also implement AI integrations with LangChain4j and Spring AI, staying current on RAG strategies, embeddings, retrieval optimization, and reranking.