Java Fullstack Developer with Gen AI
VDart Inc
- Charlotte, North Carolina, United States
- Charlotte, North Carolina, United States
About
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
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Languages
- English
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