Java Fullstack Developer with Gen AI

Java Fullstack Developer with Gen AI – VDart Inc., Charlotte, NC, United States Role Summary We are seeking a highly skilled GenAI Engineer to design, build, and operationalize next‑generation AI solutions leveraging Large Language Models (LLMs), AI agents, Retrieval Augmented Generation (RAG) architectures, and scalable cloud platforms. This role requires strong hands‑on expertise across AI concepts, model integration, data pipelines, and MLOps/CI/CD with the ability to translate business problems into production‑grade AI systems. Key Responsibilities GenAI LLM Engineering Design, develop and deploy LLM‑powered applications using leading foundation models (OpenAI, Azure OpenAI, Anthropic, open‑source LLMs) Build LLM‑based AI agents capable of multi‑step reasoning, tool use orchestration and autonomous workflows Implement and optimize agent frameworks (LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, etc.) Engineer robust prompting strategies, memory mechanisms and tool‑augmented reasoning RAG Knowledge Systems: design and implement Retrieval Augmented Generation architectures Build embedding pipelines using vector databases (FAISS, Pinecone, Weaviate, Azure AI Search, Chroma) Optimize document ingestion, chunking strategies, metadata management and re‑ranking Ensure accuracy, relevance and performance of AI‑generated responses Machine Learning Model Integration: apply practical ML concepts (classification, clustering, ranking, similarity search), integrate traditional ML models with LLM‑based systems for hybrid AI solutions, evaluate, fine‑tune and test models using appropriate performance metrics Data Engineering Pipelines: develop and maintain data pipelines for structured and unstructured data using Python and SQL; work with large datasets, APIs and streaming/batch processing frameworks; ensure data quality, lineage, observability and governance within AI workflows MLOps/CI/CD: build pipelines for AI and ML workloads including model versioning and automated testing; deploy AI services in containerized environments (Docker, Kubernetes); implement monitoring for model performance drift, latency and cost; ensure security, access control and compliance for AI systems Cloud Platform Engineering: design and deploy AI solutions on cloud platforms such as AWS, Azure or GCP, leverage managed AI/ML services, serverless components and scalable infrastructure; optimize cost, performance and reliability of AI workloads Collaboration & Stakeholder Engagement: partner with product, platform and business teams to translate requirements into AI solutions; document architectures, design decisions and operational runbooks; provide guidance on GenAI best practices, risks and responsible AI usage Core Technical Skills Strong proficiency in Python and working knowledge of SQL Solid foundation in AI/ML concepts with hands‑on experience deploying models Proven experience with LLMs, AI agents and agent frameworks Hands‑on expertise with RAG architectures and vector databases Experience implementing CI/CD pipelines for AI or ML systems Strong understanding of data pipelines and distributed data processing Experience working on at least one major cloud platform (AWS, Azure or GCP) Java – mandatory skill for the Fullstack Developer role Education Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or a related field, or equivalent practical experience What Success Looks Like Scalable, reliable GenAI solutions deployed to production Well‑architected AI agents delivering measurable business value High‑quality, explainable and maintainable AI systems Strong collaboration across engineering, data and business teams #J-18808-Ljbffr