Skills:Spring Boot~Core JavaRole Description

Java GCP Developer

As a developer, you will be responsible for the end-to-end delivery of software solutions from inception through production deployment. Work on a combination of greenfield and brownfield projects, contributing to architecture, design, development, testing, and deployment. Collaborate with peers, share technical knowledge, and contribute to engineering best practices. Apply technical expertise and industry experience to influence platform design and evolution. Mentor and guide team members while driving engineering excellence.

Build scalable, secure, and reliable enterprise applications with modern cloud and AI capabilities.

Programming

Languages:

• Java 8+
• Spring Boot
• Python
• Scala
• Node.js
• Golang
• Java Script
• C++
• C#

Cloud Platforms:

• Google Cloud Platform (GCP)
• AWS EMR

AI & Modern Engineering:

• Familiarity with AI models and AI-assisted development tools:
• Git Hub Copilot
• Codex
• Knowledge of modern AI concepts:
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• AI Agents
• Vector Databases
• Ability to integrate AI capabilities into enterprise applications securely and responsibly

Backend & Application Frameworks:

• Spring Boot
• Quarkus
• Ktor

Database Technologies:

Relational Databases:

• MySQL
• PostgreSQL
• Cloud SQL

No

SQL Databases:

• MongoDB
• Cassandra
• HBase
• Couchbase

Caching / Data Stores:

• Redis

Data & Cloud Services:

• Big Query
• Data Proc
• Dataflow
• Cloud Composer
• AWS EMR

Search, Logging & Monitoring:

• Solr
• Fluentd
• Prometheus

Containerization & Dev Ops:

Container Technologies:

• Docker

Container Orchestration:

• Kubernetes
• Google Kubernetes Engine (GKE)

CI/CD Tools:

• Jenkins
• Sonar Qube

Development Tools & Agile Practices:

• Git
• Gitflow
• Bitbucket
• Git Lab
• Jira
• Trello
• Scrum methodology

Architecture & Engineering Practices:

• Experience writing Architecture Decision Records (ADRs)
• Strong understanding of software architecture principles
• Experience designing scalable and maintainable systems
• Ability to participate in technical design discussions

AI Ecosystem

Skills:

Required Knowledge:

• LLM concepts
• RAG architecture
• AI Agents
• Vector databases
• Enterprise AI integration patterns

Good to Have:

• Lang Chain
• Prompt Engineering
• Semantic Search

Analytical &

Soft Skills:

• Applied statistics knowledge:
• Statistical distributions
• Statistical testing
• Regression analysis
• Strong creativity and problem-solving skills
• Adaptability and flexibility
• Curiosity and passion for technology
• Startup mindset and ownership mentality
• Innovative thinking
• Ability to learn and adopt emerging technologies

Key Responsibilities:

• Design, develop, test, deploy, and maintain enterprise software applications.
• Develop backend services using Java and Spring Boot.
• Build cloud-native applications using GCP services.
• Work with databases, APIs, and distributed systems.
• Implement AI-enabled solutions using modern AI frameworks and models.
• Collaborate with cross-functional teams to deliver business solutions.
• Participate in code reviews, architecture discussions, and technical mentoring.
• Continuously improve development processes and engineering practices.

Essential Keywords:

• Java 8
• Core Java
• Spring Boot
• SQL
• PostgreSQL
• MongoDB
• Google Cloud Platform (GCP)
• AI
• LLM
• RAG

Essential Skills

Summary:

Primary

Skills:

• Java 8+
• Spring Boot
• SQL/PostgreSQL
• MongoDB
• GCP
• AI/LLM/RAG

Secondary

Skills:

• Python
• Kubernetes
• Docker
• Jenkins
• Big Query
• Dataflow
• Redis
• Kafka/Streaming concepts (if applicable)
• Cloud-native architecture
• Agile development practices