Technology Architect | Cloud Platform | Google Cloud - Architecture Gen AI Engineer

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Job Title:

Technology Architect | Cloud Platform | Google Cloud - Architecture Gen AI Engineer
Work Location & Reporting Address:
Charlotte, NC 28202 (Onsite-Hybrid. LOCAL CANDIDATES ONLY!!!)
Contract duration: 12
Target

Start Date:

01 Jul 2026
Does this position require Visa independent candidates only? No

Must Have

Skills:

• GEN AI
• Agentic AI
• VLLM
• fAST API
• REST API
• MCD
• Lang Graph
• Lang Chain
• Graph RAG
• ML Ops
• Python
• ML
• Data Science
• RAG
• LLM

Nice to Have

Skills:

• GCP
• Prompt Engineering

Detailed

Job Description:

We are seeking a highly skilled Generative AI Engineer with a strong Python background to design, develop, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience with Large Language Models (LLMs), prompt engineering, and Gen AI frameworks, along with expertise in building scalable AI applications. Experience in Developing Agentic AI solutions.

Key Responsibilities:

• Design and implement Generative AI models for text, image, or multimodal applications.
• Develop prompt engineering strategies and embedding-based retrieval systems.
• Integrate Gen AI capabilities into web applications and enterprise workflows.
• Build agentic AI applications with context engineering and MCP tools.

Required Skills &

Qualifications:

• 7+ years of hands-on experience in AI, Data science, ML, GEN AI
• 2 years of strong hands on experience in Agentic AI, VLLM's, GEN AI, Lang Chain, Lang Graph, RAG, LLM OPS and AI Services in GCP and Azure.
• Strong hands on experience designing and deploying Retrieval-Augmented Generation (RAG) pipelines
• Strong MLOps/LLMOps experience with CI/CD automation,
• Extensive experience with Lang Chain, Lang Graph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
• Experience in Cloud-native engineering across AWS (Sage Maker, Lambda, ECS/Fargate, S3, API Gateway, Step Functions) and GCP (Vertex AI) for scalable AI delivery
• Experience in Developing microservices and API development using FastAPI, REST APIs, Pydantic/JSON schemas, Docker, and Kubernetes for low-latency serving.
• Strong Hands-on experience with vector databases and semantic search technologies including Pinecone, FAISS, ChromaDB, and embedding lifecycle management
• Strong proficiency in Python and AI/ML frameworks (PyTorch, Tensor Flow).
• Hands on experience using session and memory for building multi-agent systems along with using MCP tools.
• Hands-on experience with LLMs, transformers, and Hugging Face ecosystem.
• Knowledge and experience with vector databases and RAG technique for semantic search.
• Familiarity with cloud AI services (AWS Sage Maker, Azure OpenAI, GCP Vertex AI).
• Understanding of MLOps practices for scalable AI deployment.
• Strong experience in working with LLM fine-tuning with LoRA, QLoRA, PEFT,
• Strong experience in Architected advanced RAG systems using Pinecone, FAISS, Weaviate, Chroma, hybrid…