> Markdown version of [/jobs/ext/2021562-ai-developer-full-stack](https://www.wearedevelopers.com/jobs/ext/2021562-ai-developer-full-stack). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Developer - Full Stack - **Company:** Everforth Apex - **Location:** Charlotte, NC, United States (Remote available) - **Experience:** Expert - **Salary:** $143,520.0 - $153,920.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Cloud Computing, Continuous Integration, Data Masking, Python (Programming Language), Machine Learning, Node.Js, Next.js, Search Technologies, Software Engineering, SQL Databases, Google Cloud, Data Ingestion, ReactJS, Large Language Models, Multi-Agent Systems, IT Architecture, Generative AI, Backend, Fastapi, Build Management, Containerization, Kubernetes, Front End Software Development, Virtual Agents, Software Version Control, Serverless Computing, Docker - **Published:** August 11, 2026 - **Apply:** https://www.dice.com/job-detail/5c077c3b-018d-4df6-84b2-569859ec3b23 ## About the Role * 5+ years of Python development experience. * Expertise with LangChain. * Expertise with LangGraph. * Experience building and deploying production-grade GenAI applications. * Experience with Google Vertex AI, RAG architectures, and AI agent frameworks., * 7-10+ years of software engineering experience. * 3-5+ years of applied ML/GenAI experience building production systems. * Expertise with LangChain and LangGraph (tools, agents, state graphs). * Hands-on experience with Vertex AI. * Strong experience as a RAG practitioner (chunking, embeddings, hybrid retrieval, rerankers). * Experience with vector databases (Pinecone, Weaviate, Milvus, FAISS) and embedding models. * Production backend development experience in Python (FastAPI) or Node.js. * Front-end experience with React/Next.js. * Cloud experience (Google Cloud Platform preferred; AWS/Azure is a plus), Docker/Kubernetes, and CI/CD. * Understanding of GenAI evaluation (RAGAS, G-Eval), observability, and prompt/version management. * Knowledge of security and governance, including PII handling and prompt injection defenses., * Knowledge of graphs (RDF/OWL), retrieval planning, and agent patterns. * Experience with LLM serving and routing. * LlamaIndex experience. * Experience with structured RAG (SQL/Graph RAG) and function/tool calling integrations. ## Description In this contingent resource assignment, you will consult on complex initiatives with broad impact and large-scale planning for Software Engineering. This role serves as a Senior AI Developer responsible for designing, building, and productionizing enterprise GenAI applications. The successful candidate will lead the development of agentic AI workflows, Retrieval-Augmented Generation (RAG) solutions, AI orchestration frameworks, and scalable cloud-native services. This position requires experience with LangChain, LangGraph, Python development, and enterprise AI architecture while partnering closely with product, security, platform, and data teams. This is a hands-on engineering role focused on delivering secure, scalable, observable, and production-ready AI solutions., * Design and implement multi-step agentic workflows using LangChain and LangGraph. * Build complex state-machine orchestration and develop AI agents utilizing tool calling frameworks and memory components. * Design and develop enterprise RAG solutions, including ingestion pipelines for document processing, chunking, and vector indexing. * Implement hybrid retrieval, query routing, re-ranking, and semantic search to optimize retrieval accuracy. * Build and deploy solutions on Google Vertex AI, utilizing its models, endpoints, pipelines, and vector search capabilities. * Develop backend services using Python/FastAPI or Node.js and front-end applications using React/Next.js. * Containerize applications using Docker and deploy workloads to Kubernetes/GKE, supporting CI/CD automation. * Define and automate AI evaluation frameworks to measure relevance, faithfulness, latency, and cost efficiency. * Implement PII detection, data masking, audit logging, and prompt security controls to ensure compliance with enterprise standards. * Establish GenAI engineering standards and mentor other developers and AI engineers. ## Related Videos - [Building AI Applications with LangChain and Node.js](https://www.wearedevelopers.com/videos/1512-building-ai-applications-with-langchain-and-node-js) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [AI Agents Graph: Your following tool in your Java AI journey](https://www.wearedevelopers.com/videos/1550-ai-agents-graph-your-following-tool-in-your-java-ai-journey) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The State of WebDev AI 2025 Results: What Can We Learn?](https://www.wearedevelopers.com/magazine/581-the-state-of-webdev-ai-2025-results-what-can-we-learn)