Java Full Stack Developer ( Agentic AI)

Job Title-

1.Senior Java Stack Developer ( Agentic AI Must) 6+ years

2. Java Full Stack Developer ( Agentic AI Must) 2-4 years

Location - Remote (India)

Recruiter Email - [email removed]

Immediate Joiners Preferred

We are looking for an experienced Java Developer with strong expertise in backend development, cloud technologies, and emerging AI-powered automation. The ideal candidate will have hands-on experience building scalable applications using Java, Spring Boot, and Hibernate, along with deep exposure to AWS Cloud services and practical experience designing, developing, or integrating with Agentic AI systems autonomous AI agents that plan, reason, and execute multi-step workflows with minimal human intervention.

KEY RESPONSIBILITIES

Core Development

1. Design, develop, and maintain robust backend applications using Java, Spring Boot, and Hibernate
2. Build and integrate RESTful APIs and event-driven services for seamless communication between microservices and AI agents
3. Deploy and manage applications on AWS Cloud infrastructure
4. Ensure code quality, performance optimization, and adherence to best practices

Agentic AI & Generative AI

1. Design and implement AI agent workflows building autonomous agents that can plan, execute multi step tasks, invoke tools, and handle exceptions without constant human oversight
2. Develop agent orchestration patterns — manage agent-to-agent handovers, state persistence, retry logic, and fallback strategies in multi-agent systems
3. Integrate with foundation model APIs (AWS Bedrock, OpenAI, or equivalent) for LLM-powered reasoning, decision-making, and natural language understanding within agent pipelines
4. Build tool-use and function-calling interfaces that allow AI agents to interact with databases, APIs, document stores, and external services
5. Implement human-in-the-loop patterns — confidence thresholds, escalation triggers, and approval workflows where agents defer to humans on low-confidence decisions
6. Develop event-driven agent architectures using message queues (SQS/SNS, EventBridge, or Kafka) for async agent communication and workflow orchestration

Collaboration & Quality

1. Collaborate with cross-functional teams (product, data science, QA) to deliver high-quality AI-powered solutions
2. Participate in prompt engineering, agent behavior tuning, and accuracy evaluation
3. Contribute to AI-assisted development workflows using tools like Kiro, Copilot, or similar AI IDEs

REQUIRED SKILLS & EXPERIENCE

Experience - 2–8 years of professional experience in backend/fullstack development

Core Backend - Strong proficiency in Java (11+), Spring Boot, and Hibernate/JPA

APIs - Hands-on experience designing and integrating RESTful APIs and webhook based integrations

Cloud (AWS) - Working knowledge of AWS services — EC2, S3, Lambda, SQS/SNS, EventBridge, API Gateway, Cognito

Agentic AI - Experience building or integrating with autonomous AI agent systems — multi step workflows, tool-use patterns, agent orchestration, state management

Generative AI - Hands-on experience with LLM APIs (AWS Bedrock, OpenAI, Anthropic, or similar) — prompt engineering, function calling, structured output parsing

Databases - Proficiency with relational databases (PostgreSQL, MySQL) — schema design, query optimization

Architecture - Understanding of event-driven and microservices architecture patterns

Problem-Solving - Excellent analytical, problem-solving, and communication skills

GOOD TO HAVE

AGENTIC AI & ADVANCED AI

1. Experience with AI agent frameworks (AWS AgentCore, LangChain, LangGraph, CrewAI, AutoGen, or custom agent orchestrators)
2. Familiarity with Retrieval-Augmented Generation (RAG) patterns — vector databases, embeddings, document retrieval
3. Experience with confidence scoring, human-in-the-loop decision systems, and AI output validation
4. Exposure to multi-agent systems where multiple specialized agents collaborate on complex workflows
5. Experience building AI agents that interact with external APIs, document processing services, or third party platforms via tool-use/function-calling
6. Familiarity with prompt management, A/B testing prompts, and agent behavior evaluation

PLATFORM & DEVOPS

1. Experience with Microservices Architecture at scale
2. Knowledge of CI/CD pipelines (GitHub Actions, Jenkins) and Docker/Kubernetes
3. Infrastructure as Code (Terraform, AWS CDK)
4. Experience with Amazon ECS/EKS for container orchestration
5. Familiarity with observability tools (CloudWatch, X-Ray, Grafana) for monitoring agent pipelines

DEVELOPMENT PRACTICES

1. Exposure to Agile methodologies
2. Experience with AI-assisted development tools (Kiro, GitHub Copilot, or similar)
3. Understanding of async processing patterns (event sourcing, CQRS, saga patterns)
4. Experience with document processing or OCR integration (Textract, Ocrolus, or similar)

WHAT SETS THIS ROLE APART

This is not a traditional backend role. You'll be building systems where AI agents are first-class participants in business workflows — making decisions, invoking services, handling exceptions, and coordinating with other agents autonomously.

You'll need to think about:

1. How agents maintain context and state across multi-step operations
2. How to design reliable failover when an agent encounters an unexpected scenario
3. How to balance autonomy (letting agents act) vs. control (humans approving)
4. How to test and validate non-deterministic AI agent behavior in production systems

AGENTIC AI SKILLS SPECTRUM

LEVEL & WHAT WE'RE LOOKING FOR:

Minimum - Has integrated LLM APIs into applications, understands prompt engineering, built at least one multi-step automated workflow using AI

Preferred - Has designed agent orchestration patterns, built tool-calling interfaces, implemented human-in-the-loop escalation, worked with agent frameworks

Ideal - Has architected multi-agent systems in production, designed agent state management, built agent observability/evaluation, managed agent reliability in production