Lead Java Developer - AI & Full Stack Solutions

Cliff Services Inc

Phoenix, AZ, United States

26 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

2 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services HTML5 Microsoft Azure Cascading Style Sheets (CSS) Cloud Computing Code Review Continuous Integration DevOps Payment Systems

+35 more

Github Node.Js Performance Tuning RabbitMQ Software Engineering Systems Integration TypeScript User-Centered Design Web Applications Web Application Frameworks Privacy Controls Google Cloud Enterprise Software Applications Spring Cloud ReactJS Retrieval-Augmented Generation Large Language Models Spring-boot Generative AI Backend Vue.js Event Driven Architecture AngularJS Integration Tests Kubernetes Information Technology Apache Kafka Graphql Web Technologies Front End Software Development Restful APIs Docker Service Stack Jenkins Microservices

Job description

We are looking for a highly skilled Lead Java Developer with expertise in Artificial Intelligence (AI), Generative AI (LLMs, RAG, MCP), and Full Stack Development to design and build next-generation enterprise applications. In this role, you will lead the architecture, engineering, and deployment of resilient, AI-powered enterprise microservices and customer-facing web applications.

The ideal candidate brings strong hands-on experience in Java core platform engineering, integration with modern AI architectures (Retrieval-Augmented Generation, Model Context Protocol, and Large Language Models), and modern frontend frameworks (React/Angular/Node.js)., * Technical Leadership & Architecture: Lead the end-to-end design, development, and architectural delivery of scalable, secure Java-based backend microservices integrated with advanced AI/LLM capabilities.

AI & LLM Integration: Design and implement RAG (Retrieval-Augmented Generation) pipelines, integrate MCP (Model Context Protocol) servers/tools, vector databases, and enterprise LLM orchestration framework (e.g., Spring AI, LangChain4j, Semantic Kernel).
Full Stack Execution: Oversee and contribute to full stack development-connecting modern frontend frameworks (React.js, Angular, or Vue.js) with AI-enhanced RESTful and GraphQL APIs.
Enterprise Security & Governance: Implement enterprise-grade security, data protection, privacy controls, and API governance suitable for large-scale financial and payment systems.
Engineering Best Practices: Drive code reviews, automated unit/integration testing, CI/CD pipeline automation, observability/monitoring, and performance tuning across the cloud stack (AWS/Google Cloud Platform/Azure).
Mentorship & Collaboration: Guide and mentor software engineers, partner closely with Data Scientists, AI Engineers, Product Managers, and Solution Architects to translate business requirements into technical reality.

Requirements

Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
Core Java Leadership: 8+ years of hands-on Java engineering experience (Java 17/21, Spring Boot, Spring Cloud, Microservices, Event-driven architecture with Kafka/RabbitMQ).
AI / GenAI Expertise: 2+ years of practical experience integrating AI capabilities into enterprise applications:
Building RAG pipelines utilizing Vector Databases (e.g., Pinecone, Milvus, pgvector, Qdrant).
Hands-on familiarity with MCP (Model Context Protocol) standards, tools, and agentic workflows.
Integration with LLM APIs (OpenAI, Anthropic Claude, Llama, Bedrock, Vertex AI) using Spring AI or LangChain4j.
Full Stack Development: Proficiency in frontend web technologies (React.js, Angular, TypeScript, HTML5/CSS3) and backend API integrations.
Cloud & DevOps: Deep expertise in Cloud platforms (AWS/Azure/Google Cloud Platform), Docker, Kubernetes, CI/CD pipelines (Jenkins/GitHub Actions), and infrastructure-as-code.
Location: Based in or willing to work onsite/hybrid in Phoenix, AZ.