Job Title: Full Stack Developer – GenAI / Agentic AI
Location: Charlotte, NC
Experience: Mid-Senior Level
Job Summary:
We are seeking a skilled Full Stack Developer with expertise in Java, Reactive programming, Conversational AI, and Generative AI. The ideal candidate will develop scalable backend services and modern AI-powered applications using Google Vertex AI, Agentic AI frameworks, and RAG architectures. Experience with Google ADK, LangChain, and AI agent integration is highly desirable.
Key Responsibilities:
- Design, develop, and maintain full-stack applications using Java, Spring Boot, and modern front-end technologies.
- Build reactive backend services using Spring WebFlux and Reactive Java.
- Develop and integrate RESTful APIs and microservices for enterprise applications.
- Implement event-driven architectures using Apache Kafka and Redis.
- Design and develop Conversational AI solutions using Google Vertex AI and Generative AI technologies.
- Build and orchestrate AI agents using Google ADK or similar agent development frameworks.
- Implement RAG pipelines using LangChain, embeddings, and vector search technologies.
- Develop and integrate MCP servers and enable Agent-to-Agent (A2A) communication.
- Perform AI evaluations, monitor model performance, and implement observability practices.
- Develop and execute Python-based automated tests using pytest.
- Collaborate with cross-functional teams to deliver secure, scalable, and reliable AI-powered applications.
Required Qualifications:
- Strong hands-on experience in Java full-stack development.
- Expertise in Spring WebFlux, Reactive Java, RESTful APIs, and microservices.
- Experience with Apache Kafka, Redis, and software architecture principles.
- Hands-on experience with Generative AI, Conversational AI, and Agentic AI.
- Experience with Google Vertex AI and building AI agents, preferably using Google ADK.
- Strong knowledge of Python programming and LangChain.
- Experience implementing Retrieval-Augmented Generation (RAG) architectures.
- Familiarity with AI evaluations (Evals), model monitoring, and observability.
- Experience with MCP servers and Agent-to-Agent (A2A) communication.
- Experience writing automated Python tests using pytest.
Preferred Qualifications:
- Knowledge of Neo4j and graph database concepts.
- Experience with embeddings, vector databases, and semantic search.
- Familiarity with cloud-native application development and CI/CD pipelines.
- Strong analytical, problem-solving, and communication skills.