Java Full Stack Developer - Agentic AI / LLM Integration

Job Title: Java Full Stack Developer with LLM
Type: Hybrid (TX, Boston)
Duration: 12+
Summary:
We're looking for a Java Full Stack Developer with deep backend engineering skills and real production experience embedding Large Language Model (LLM) capabilities into enterprise-grade applications. You'll architect scalable microservices with Spring Boot, design agentic AI workflows with LangChain4j or Spring AI, and own AI-powered features end to end - from React frontends to cloud-deployed backends. Expect to build resilient LLM integration patterns and set technical best practices across the team.

What You'll Do

• Design and build scalable RESTful microservices and APIs in Java 17/21 and Spring Boot, applying cloud-native and domain-driven design principles.

• Architect LLM-powered features with LangChain4j or Spring AI - tool/function calling, agentic chains, RAG pipelines, and prompt engineering.

• Integrate LLM providers (OpenAI, Azure OpenAI, AWS Bedrock, Anthropic Claude) into production with proper guardrails, hallucination mitigation, and evaluation frameworks.

• Build fault-tolerant service integrations using Feign clients and Resilience4j (circuit breakers, retries, rate limiters) for reliability against upstream failures.

• Implement asynchronous workflows on Kafka (or similar); design job-ID-based async response patterns for long-running operations.

• Develop and maintain React front-end components that consume REST APIs and handle loading, error, and success states cleanly.

• Manage conversation state and session context in MongoDB or equivalent NoSQL stores to power multi-turn AI interactions and follow-up reasoning.

• Collaborate with product, QA, and platform teams in Agile sprints; contribute to design reviews, code reviews, and technical documentation.

What You Bring

• 8+ years of professional Java development; strong command of Java 17/21 features including virtual threads and modern concurrency patterns.

• Proven expertise with Spring Boot, Spring Security, Spring Data JPA, and microservices architecture; experience with API Gateway patterns and JWT-based authentication.

• Hands-on experience integrating LLMs via APIs (OpenAI, Azure OpenAI, AWS Bedrock, or Anthropic); practical knowledge of prompt engineering, RAG, embeddings, and vector databases.

• Experience with LangChain4j, Spring AI, or equivalent Java-native LLM frameworks for agentic, tool-calling, or multi-step AI orchestration.

• Proficiency in front-end development with React.js - building, debugging, and optimizing component-based UIs and REST API integrations.

• Solid grasp of asynchronous messaging (Kafka, RabbitMQ), distributed systems patterns, and cloud deployment (AWS, Azure, or GCP).

• Ability to deploy and fine-tune LLM models on devices such as computers, routers, etc.; experience with Model APIs.