Senior Agentic AI + JAVA engineer/architect

Agentic AI engineer with prior great J2EE experience who can design agents, design MCP servers to connect various nodes of J2EE and make entire cycle agentic

Location : Charlotte, North Carolina, United States (USA) Onsite

We are seeking a Senior Agentic AI Engineer with strong J2EE/Java engineering experience to design and build an agentic AI ecosystem around complex enterprise J2EE applications.

The engineer will design specialized AI agents and Model Context Protocol (MCP) servers that securely expose application components, repositories, APIs, databases, build/test systems, documentation, and other enterprise tools to agents. The objective is to create an end-to-end agentic software engineering and modernization lifecycle, covering application discovery, impact analysis, development, testing, validation, deployment support, and operational knowledge.Design and implement AI agents and multi-agent workflows for enterprise J2EE applications.

• Architect MCP servers, tools and resources that provide controlled access to different nodes/components of the J2EE ecosystem.
• Connect agents with:
• Java/J2EE source repositories
• Spring / Spring Boot applications
• REST/SOAP APIs
• Application servers and middleware
• Databases and SQL
• Messaging systems
• Build pipelines
• Test automation frameworks
• Application documentation and knowledge repositories
• Design specialized agents for:
• Code analysis
• Dependency discovery
• Impact analysis
• Code generation/refactoring
• Unit and integration testing
• Code review
• Defect analysis
• Documentation
• Deployment-readiness validation
• Build orchestration patterns where multiple agents collaborate to execute end-to-end engineering workflows.
• Develop agent memory/context strategies for understanding large and complex J2EE applications.
• Design tool-calling and MCP patterns with appropriate authentication, authorization, auditability and human-in-the-loop controls.
• Define guardrails to prevent uncontrolled code changes or production actions.
• Integrate agentic solutions with enterprise Git/Bitbucket, CI/CD, APIs, databases and engineering platforms.
• Build reusable agent/MCP frameworks that can scale across multiple applications rather than developing application-specific prototypes.
• Partner with application architects, engineering teams, DevOps and AI teams to identify high-value opportunities for agentic automation.
• Establish observability and evaluation mechanisms to measure agent accuracy, execution success, failures and human intervention.

Required Technical Skills

Java / J2EE

• Strong hands-on experience with Java, J2EE, Spring and Spring Boot
• REST/SOAP services and enterprise integration
• JDBC/JPA/Hibernate
• JMS or equivalent messaging technologies
• Maven/Gradle
• JUnit and automated testing
• Enterprise application architectures and design patterns

Agentic AI

• Strong understanding of:
• LLM-based agents
• Agent orchestration
• Tool/function calling
• Prompt/context engineering
• RAG
• Agent memory
• Multi-agent architectures
• Human-in-the-loop workflows
• Agent evaluation and observability

MCP

• Hands-on ability to design and develop Model Context Protocol servers
• Ability to expose enterprise tools, APIs, repositories and application capabilities as MCP tools/resources
• Understanding of secure MCP architecture, authentication, authorization and access controls

AI Engineering

• Python and/or Java-based AI integration
• Experience with frameworks such as Semantic Kernel, LangGraph, LangChain or equivalent agent orchestration frameworks
• Experience integrating enterprise LLM platforms such as Azure OpenAI/OpenAI or equivalent

DevOps / Engineering Integration

• Git / Bitbucket
• CI/CD pipelines
• Jenkins, GitHub Actions, Azure DevOps or comparable platforms
• Docker/Kubernetes exposure
• API-based enterprise integrations

Preferred Experience

• 8 years of overall software engineering experience with substantial Java/J2EE development experience.
• Recent hands-on experience designing GenAI/Agentic AI solutions.
• Experience modernizing large legacy Java/J2EE platforms.
• Experience creating MCP servers and agent-to-tool integrations.
• Experience building production-grade agentic solutions rather than only chatbots/POCs.
• Banking, financial-services, payments, or other highly regulated enterprise experience is highly desirable.

Department : Cloud & Data Engineering

Years of Experience : 8 to 10