GenAI Engineer - Orlando, FL, Columbia, SC, Atlanta, GA, Charlotte, NC, Tampa, FL, Raleigh, NC, Durham, NC.

Job Title: GenAI Engineer 
Location: Orlando, FL, Columbia, SC, Atlanta, GA, Charlotte, NC, Tampa, FL, Raleigh, NC, Durham, NC.
Looking for W2 candidates. No C2C

Job Summary
We are looking for an experienced GenAI Engineer to design and build next-generation AI applications using Google Gemini, Vertex AI, and the Google Cloud Platform (Google Cloud Platform) ecosystem. The ideal candidate will have strong expertise in LangChain, LangGraph, Retrieval-Augmented Generation (RAG), agentic AI workflows, and scalable cloud-native architectures. This role involves building production-grade AI solutions, integrating LLMs into enterprise applications, and developing intelligent multi-agent systems.

Key Responsibilities
•    Design, develop, and deploy Generative AI applications powered by Google Gemini (Pro, Flash, Ultra) and Vertex AI.
•    Build advanced prompt pipelines, RAG applications, and AI workflows using LangChain.
•    Design and implement stateful, multi-agent AI systems using LangGraph.
•    Develop scalable AI solutions utilizing Google Cloud services including Vertex AI Search, BigQuery, Cloud Run, Cloud Storage, and IAM.
•    Build robust data ingestion pipelines supporting multiple document formats.
•    Implement vector search architectures using Vertex AI Vector Search or vector databases such as Chroma, Milvus, Pinecone, Weaviate, or Qdrant.
•    Optimize LLM performance using prompt engineering, few-shot learning, and PEFT techniques.
•    Establish evaluation metrics for LLM accuracy, latency, hallucination detection, and model performance.
•    Implement LLMOps best practices including observability, scalability, monitoring, and security.
•    Develop REST APIs using FastAPI or Flask to expose AI services.
•    Collaborate with Product Managers, Data Engineers, and Front-End Developers to integrate AI capabilities into enterprise applications.

Required Qualifications
•    Strong programming experience in Python.
•    Experience building REST APIs using FastAPI or Flask.
•    Hands-on experience with Google Gemini APIs, Vertex AI, and other enterprise LLM platforms.
•    Strong expertise with Langchain and LangGraph.
•    Experience implementing RAG architecture.
•    Strong knowledge of Google Cloud Platform (Google Cloud Platform).
•    Experience with Vertex AI, IAM, Cloud Run, BigQuery, and Google Cloud Storage.
•    Experience working with Vector Databases including Pinecone, Weaviate, Qdrant, Chroma, or Milvus.
•    Strong SQL and NoSQL database experience.
•    Experience debugging complex AI pipelines and distributed applications.
•    Strong problem-solving and communication skills.

Preferred Qualifications
•    Google Cloud Professional Machine Learning Engineer Certification.
•    Google Cloud Professional Cloud Architect Certification.
•    Experience with Llama Index.
•    Experience with Hugging Face.
•    Experience with React and TypeScript.
•    Knowledge of Agentic AI architectures.
•    Experience with MLOps or LLMOps platforms.

Required Skills
•    Python
•    Google Gemini
•    Vertex AI
•    Google Cloud Platform (Google Cloud Platform)
•    Langchain
•    LangGraph
•    FastAPI
•    Flask
•    RAG
•    Prompt Engineering
•    Vector Databases
•    Pinecone
•    Weaviate
•    Qdrant
•    Chroma
•    Milvus
•    BigQuery
•    Cloud Run
•    Google Cloud Storage
•    REST APIs

Preferred Skills
•    Llama Index
•    Hugging Face
•    React
•    TypeScript
•    PEFT
•    LLMOps
•    Agentic AI
•    Vertex AI Vector Search
•    Few Shot Learning
•    Cloud Architecture

Best Regards: 
Lucy Rose
Phone: +1-
Email: