Full Stack Developer

Job Title

Job Type

Company

• Confidential – Would be disclosed once the candidate is finalized

Work Schedule

• Standard:
• Sunday to Friday
• Weekend work may be required occasionally for critical client deliveries (not regular)

Contract Structure

• **6 Months’ Probation**
• Followed by

Role Overview

Mid to Senior Full Stack Java Developer

Full Stack & Enterprise Application Development

• Design and develop
• enterprise-grade full stack applications
• using:
• **Java JDK 20/22**
• **Jersey or Spring Framework**
• for API services
• **Angular 19/22**
• for frontend UI development
• Develop scalable, secure, and high-performance REST APIs
• Implement ORM-based persistence using

Middleware & Event-Driven Architecture

• Design and develop middleware using:
• **RabbitMQ and/or Apache Kafka**
• Build event-driven, asynchronous, and distributed processing workflows

AI/LLM-Driven Engineering & Platform Development

• Design and implement
• company-wide AI/LLM infrastructure
• to support:
• AI-driven development assistance
• AI-driven test case generation and automation
• AI-driven documentation generation
• AI-driven code reviews and quality checks
• AI-driven requirement analysis and user story generation
• Build and integrate
• LLM-powered agents
• to automate SDLC activities across:
• Development
• Testing
• QA
• Documentation
• Release validation
• Integrate with
• LLM platforms (OpenAI, Azure OpenAI, local/private LLMs, etc.)
• Design application-level
• AI orchestration layers
• and agent workflows
• Implement
• prompt engineering, context management, and model integration patterns
• Build
• secure, auditable, and governed AI usage
• within enterprise applications

Enterprise AI Architecture & Governance

• Design
• enterprise AI architecture
• for application-level AI capabilities
• Define patterns for:
• AI service abstraction layers
• LLM gateway services
• Prompt/version management
• Model routing and fallback strategies
• Logging, monitoring, and audit trails for AI interactions
• Support data governance, security, and compliance for AI usage

Security & Secure Coding

• Apply enterprise
• secure coding practices
• across all layers
• Implement authentication, authorization, encryption, and vulnerability mitigation
• Ensure security for both application code and
• AI/LLM integrations

Test Driven Development (TDD) & AI-Assisted QA

• Strong adherence to

Test Driven Development (TDD)

• Implement:
• Unit testing
• Integration testing
• API automation
• Leverage AI tools and agents to:
• Generate test cases
• Identify edge cases
• Improve test coverage
• Automate regression validation

DevOps, Docker & AI Platform Deployment

• Build and deploy containerized applications using

Docker

• Deploy and manage:
• Application services
• AI services
• LLM gateways
• Agent orchestration components
• Support CI/CD integration for both application and AI services

SDLC, Architecture & Design Ownership

• Actively contribute to and author:
• **High Level Design (HLD)**
• **Low Level Design (LLD)**
• **System Architecture diagrams**
• **AI architecture diagrams**
• **UI/UX flows and wireframes**
• **Workflow diagrams**
• **User stories and acceptance criteria**
• **Data models and persistence strategies**
• **AI integration and governance documents**

Client Interaction & AI Enablement

• Work directly with clients on:
• Functional and technical requirements
• AI-enabled solution design
• AI use case identification
• AI platform demonstrations and enablement
• Support enterprise clients in adopting
• AI-driven development and automation practices

Tools, Process & AI-Augmented Delivery

• Use

JIRA

• and QA tools for delivery tracking
• Use AI tools and agents to:
• Accelerate delivery
• Improve code quality
• Reduce manual effort
• Enhance documentation accuracy

Backend

• Java

Jdk 20/22

• **Jersey or Spring Boot / Spring MVC**
• **Hibernate / Spring Data JPA**
• REST API design & development

Frontend

• **Angular 19/22**

Middleware

• **RabbitMQ**
• **Apache Kafka**

AI / LLM Platforms & Tooling

• Experience working with:
• LLM APIs (OpenAI, Azure OpenAI, Anthropic, etc.)
• Local/private LLMs (optional but preferred)
• AI agent frameworks (preferred)
• Prompt engineering and context management
• AI workflow orchestration concepts
• AI logging, monitoring, and governance concepts

Security

• Secure coding best practices
• Authentication & authorization
• OWASP Top 10 awareness and mitigation
• Security for AI integrations

• Test Driven Development (TDD)

• JUnit, Mockito, API testing frameworks
• AI-assisted test generation (preferred)

DevOps

• **Docker**
• CI/CD exposure preferred

Tools

• **JIRA**
• QA and defect tracking tools

Required Experience & Profile

• Mid to Senior level experience in enterprise full stack development
• Strong experience in designing and building
• secure, scalable enterprise systems
• Demonstrated experience integrating or architecting
• AI/LLM-driven solutions
• Experience building or contributing to
• enterprise AI platforms or internal AI tooling
• Strong documentation and architecture ownership
• Client-facing experience with strong communication skills

Preferred Qualifications

• Experience with private/on-prem LLM deployments
• Experience with AI governance and compliance
• Experience building internal developer platforms or AI developer tools
• Experience with microservices and distributed architectures
• Experience supporting global enterprise or Middle East clients