Full Stack Java Developer Agentic AI

Job Description

Job Description Job Description
Our client is seeking a Full Stack Java Developer with Agentic AI experience to build and enhance enterprise applications within a financial services environment. The ideal candidate will have strong hands-on experience in Java backend development, modern front-end technologies, and practical experience building AI-powered applications using Agentic AI frameworks and Large Language Models (LLMs).
Responsibilities

• Design, develop, and maintain full-stack enterprise applications using Java and modern front-end technologies.
• Build scalable REST APIs and microservices using Java and Spring Boot.
• Develop responsive user interfaces using React, Angular, or similar frameworks.
• Design and implement Agentic AI solutions utilizing LLMs to automate business workflows and improve user experiences.
• Integrate AI services into enterprise applications and optimize AI-driven processes.
• Collaborate with product owners, architects, QA, and business stakeholders throughout the SDLC.
• Participate in Agile ceremonies, code reviews, testing, and production support.
• Ensure application performance, security, scalability, and maintainability.

Required Qualifications

• 8 years of Full Stack Java development experience.
• Strong hands-on experience with Java, Spring Boot, Microservices, REST APIs, and modern backend development.
• Experience with React, Angular, or similar JavaScript frameworks.
• Hands-on experience with Agentic AI, LLMs, LangChain, LangGraph, CrewAI, AutoGen, or similar AI orchestration frameworks.
• Experience integrating AI capabilities into enterprise applications.
• Strong knowledge of SQL/NoSQL databases.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with CI/CD pipelines, Git, Docker, and Kubernetes.
• Strong problem-solving, communication, and stakeholder collaboration skills.
• Ability to work EST business hours.

Preferred Qualifications

• Experience in the Financial Services domain.
• Exposure to RAG (Retrieval-Augmented Generation), vector databases, and prompt engineering.
• Experience with DevOps and cloud-native application development.
• Familiarity with secure coding practices and enterprise architecture.