Senior Full Stack Java Engineer – AI & Cloud

Job Title: Senior Full Stack Java Engineer – AI & Cloud

Experience: 10+ Years

Employment Type: Full-Time

Location: Chennai,

Position Overview

We are seeking a Senior Full Stack Java Engineer with deep expertise in Java, Microservices, Cloud Architecture, and hands-on experience integrating AI/LLM capabilities into enterprise-grade applications. This role focuses on building production-ready software systems that leverage AI as an accelerator to enhance application intelligence and user experience—not on developing core AI/ML models.

The candidate will be involved across the entire Software Development Life Cycle (SDLC), from requirement analysis and architecture design to development, testing, deployment, and continuous optimization.

Key Responsibilities

1. Engage with customers and stakeholders to deeply understand use cases, pain points, and business requirements, advocating user-centric software solutions.
2. Design, develop, test, and deliver scalable full-stack applications using modern tools, frameworks, and Agile methodologies.
3. Assess software requirements and determine appropriate technology stack, cloud architecture, integration methods, and deployment strategies.
4. Design high-level and low-level software architecture, defining system components, interfaces, and data flows.
5. Collaborate closely with cross-functional teams including product owners, UX designers, architects, QA, and DevOps.
6. Define and implement software testing strategies, standards, and processes aligned with organizational goals and industry best practices.
7. Continuously improve application performance, scalability, security, and reliability.
8. Apply modern engineering practices such as TDD, CI/CD, and DevOps automation.
9. Implement and support security best practices, including encryption, anonymization, OAuth 2.0, JWT, and API security standards.
10. Develop responsive, user-friendly front-end interfaces using Angular or similar frameworks.
11. Design and build backend services, REST APIs, and microservices using Java and Spring Boot.
12. Integrate LLMs and AI services into business applications, including prompt engineering and AI tool orchestration.
13. Evaluate and adopt emerging technologies, particularly in GenAI, Cloud, and AI-agent ecosystems.

Primary Skills Required

• Core Java (Java 8 / 11 / 17 / 21)
• Spring Framework (Spring Boot, Spring MVC, Spring Security, Spring Data)
• RESTful API Design & Development
• Microservices Architecture (API Gateway, Service Discovery, Circuit Breaker, CQRS, Event Sourcing)
• Full Stack Development (Angular preferred)
• Cloud Platforms: GCP (preferred), AWS, or Azure
• AI Integration:
• Spring AI
• LangChain4j
• Google Agent Development Kit (ADK)
• Model Context Protocol (MCP)
• Prompt Engineering & Context Management
• CI/CD, Git, DevOps practices
• Containerization: Docker, Kubernetes

Must-Have Experience

• 10+ years of overall IT industry experience
• Strong expertise in:
• Object-Oriented Design & Design Patterns (GoF)
• Full SDLC: requirements, design, development, testing, deployment
• Unit testing frameworks: JUnit, Mockito, TestNG
• 2+ years of hands-on experience integrating AI/LLM capabilities into enterprise applications
• Experience with:
• LLM integration into business workflows
• AI tool calling patterns and MCP
• API security (OAuth 2.0, JWT)
• Strong troubleshooting and performance optimization skills
• Experience with application monitoring tools (Dynatrace or similar)

Preferred / Nice-to-Have Skills

• Python & AI/ML Ecosystem
• Python programming
• TensorFlow, PyTorch, Scikit-learn
• Agentic frameworks: CrewAI, LangChain, AutoGen
• Advanced AI integrations:
• Google ADK
• MCP
• AI agent orchestration patterns
• Data & Messaging:
• Apache Kafka, Apache Spark
• Databases:
• RDBMS: Oracle, PostgreSQL, MySQL
• NoSQL: MongoDB, Cassandra, Redis
• Vector Databases & RAG (Retrieval-Augmented Generation)
• GCP Services:
• BigQuery, Cloud Run, Cloud Functions, Vertex AI
• Enterprise Security:
• SSO, ADFS, Azure AD, SAML
• Infrastructure as Code:
• Terraform
• Frontend:
• React (nice to have)
• Agile & DevOps best practices

Education Required

• Bachelor’s Degree in Computer Science, Engineering, or related field

Additional Information

The ideal candidate is a strong Java engineer with an AI-first mindset, who uses AI to enhance application capabilities rather than focusing on model training. A solid foundation in enterprise software engineering, system design, and cloud-native architecture is essential, with AI acting as a powerful enabler for innovation and efficiency