Demo

Technology Architect | Cloud Platform | Google Cloud - Architecture

Expedite Talent Solutions
Charlotte, NC Full Time
POSTED ON 9/12/2026
AVAILABLE BEFORE 1/9/2027
Description: POC: Sam Chavez

ATTENTION ALL SUPPLIERS!!!

READ BEFORE SUBMITTING:

  • UPDATED CONTACT NUMBER and EMAIL ID is a MANDATORY REQUEST from our client for all the submissions
  • We prioritize endorsing those with complete and accurate information
  • Avoid submitting duplicate profiles. We will Reject/Disqualify immediately.
  • Make sure that candidate's interview schedules are updated. Please inform the candidate to keep their lines open.
  • Please submit profiles within the max proposed rate***
  • Please make sure to TAG the profiles correctly if the candidate has WORKED FOR *** as a SUBCON or FTE.

MANDATORY: Please include in the resume the candidate’s complete & updated contact information (Phone number, Email address and Skype ID) as well as a set of 5 interview timeslots over a 72-hour period after submitting the profile when the hiring managers could potentially reach to them. PROFILES WITHOUT THE REQUIRED DETAILS and TIME SLOTS will be REJECTED.

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

MAX VENDOR RATE: *** per hour max

Target Start Date: 01 Jul 2026

Does this position require Visa independent candidates only? Yes

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 LangChain, LangGraph, and agentic AI patterns including routing, memory, multi-agent orchestration, guardrails, and failure recovery.
  • Experience in Cloud-native engineering across AWS (SageMaker, 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, TensorFlow).
  • 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 SageMaker, 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 retrieval, and custom embeddings,
  • Strong experience in Designing end-to-end LLMOps/MLOps pipelines using MLflow, DVC, SageMaker Pipelines, Vertex AI Pipelines, and GitHub Actions
  • Experience in using cloud-native AI systems on AWS (SageMaker, Lambda, EKS, EC2, Step Functions, S3, Glue) and GCP Vertex AI, supporting high-volume inference and secure enterprise operations
  • Experience in developing multi-agent orchestration workflows using LangGraph and CrewAI for tool-calling, validation agents, automated reasoning, and workflow supervision

Minimum Years of Experience:

  • 10 years

Certifications Needed:

Top 3 responsibilities you would expect the Subcon to shoulder and execute:

  • Strong experience in GEN AI, LLM, RAG,ML, DL,ML Ops, LLMOps, Cloud platform,Model servicing optimization, Python
  • Strong communication skills
  • Strong programming skills

Interview Process (Is face to face required?)

  • Face to face interview

Any additional information you would like to share about the project specs/nature of work:

Custom Fields:

Name: Intake Call Completed

Value: true

Name: Intake Call Requested

Value: true

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