Technology Architect | Cloud Platform | Google Cloud - Architecture – Gen AI Engineer
ClifyX· enterprise· Staffing And Recruiting· Sep 24, 2026 · 1mo ago
Charlotte, NC
Hybrid
Contract
Mid
$100K–$160K est.
2+ years exp
Job description
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 INFOSYS 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
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 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
Application prep
Use the role’s language and application details while tailoring your materials.
Keywords to mirror
aiapirestmlpythonllmgcpazureci/cdawsdockerkubernetes
- Platform
- jobdiva
- Effort
- medium
Benefits
Benefits detected in the listing.
Vision