AI/Full Stack Engineer (GCP, LLM, Graph RAG)

Tasks

• Design, develop, and deploy full stack applications using React, Node.js, and Python
• Build and integrate LLM-powered solutions using APIs such as Vertex AI, Gemini, OpenAI, or Anthropic
• Implement RAG (Retrieval-Augmented Generation) pipelines, including chunking, embedding, vector search, and re-ranking
• Develop and optimize Graph RAG architectures, leveraging graph data to enhance LLM responses
• Work with graph databases (Neo4j, Spanner Graph, or similar) for schema design and query development
• Build and deploy applications on Google Cloud Platform (GCP) including Cloud Run, BigQuery, Pub/Sub, and GCS
• Design and maintain Elasticsearch indices and implement search functionality using query DSL
• Develop and manage agentic workflows using LangGraph, including multi-agent systems and human-in-the-loop patterns
• Collaborate with cross-functional teams to deliver scalable and production-ready AI solutions
• Monitor and improve model performance using tools such as Galileo for evaluation and hallucination detection

Requirements

• 4+ years of full stack development experience across frontend and backend
• Strong proficiency in React, Python, and Node.js
• Hands-on experience with GCP services (Vertex AI, Cloud Run, BigQuery, Pub/Sub, Load Balancer, GCS)
• Experience working with graph databases (Neo4j, Spanner Graph, or similar)

Schedule

• Contract
• Onsite

How to apply

• Share resumes by email

Location

• Dallas, TX / Tampa, FL