Skills: Spring Boot~Core Java
Role Description

• 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.

Required Technical Skills

Programming Languages

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

Cloud Platforms

• Google Cloud Platform (GCP)
• AWS EMR

AI & Modern Engineering

• Familiarity with AI models and AI-assisted development tools:
  • GitHub 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

NoSQL Databases

• MongoDB
• Cassandra
• HBase
• Couchbase

Caching / Data Stores

• Redis

Data & Cloud Services

• BigQuery
• DataProc
• Dataflow
• Cloud Composer
• AWS EMR

Search, Logging & Monitoring

• Solr
• Fluentd
• Prometheus

Containerization & DevOps

Container Technologies

• Docker

Container Orchestration

• Kubernetes
• Google Kubernetes Engine (GKE)

CI/CD Tools

• Jenkins
• SonarQube

Development Tools & Agile Practices

• Git
• Gitflow
• Bitbucket
• GitLab
• 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

• LangChain
• 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
• BigQuery
• Dataflow
• Redis
• Kafka/Streaming concepts (if applicable)
• Cloud-native architecture
• Agile development practices