Placement Role - Cloud /AI Architect with RAG and Agentic AI with AWS/ Google Cloud Platform Exp (Hybrid) - CT

Need

Placement Role: Cloud /AI Architect with RAG and Agentic AI with AWS Experience (Hybrid 1-2 days Onsite/ Week)

(Direct Client)

Location: Stamford, CT

Duration: 12-18+ Months

JOB DESCRIPTION:
Cloud/AI Architect to design and build enterprise-grade agentic AI systems. This role will focus on architecting scalable AI solutions using AWS Agent Core or Google Cloud Platform-native AI services, driving the technical strategy for how our organization builds, deploys, and governs autonomous AI agents and knowledge retrieval systems.
Key Responsibilities

• Architect and implement agentic AI pipelines (multi-step reasoning, tool use, orchestration) using AWS Agent Core, Google Cloud Platform Vertex AI, or equivalent frameworks
• Design and build enterprise RAG systems, including data ingestion, chunking strategies, embedding pipelines, vector store integration, and retrieval optimization
• Define cloud architecture patterns for AI workloads compute, storage, networking, security, and cost optimization
• Evaluate and select appropriate LLM providers, orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, Bedrock Agents), and vector databases (e.g., OpenSearch, Pinecone, pgvector)
• Collaborate with data engineering, security, and platform teams to ensure AI solutions meet enterprise standards for scalability, reliability, and compliance
• Build reusable architectural blueprints and reference implementations for agentic AI and RAG use cases across business units
• Provide technical leadership and mentorship to engineering teams implementing AI solutions
• Stay current with evolving cloud AI services and recommend adoption where it drives business value
• Partner with stakeholders to translate business requirements into scalable, production-ready AI architecture
• Experience standing up agentic AI governance frameworks guardrails, audit trails, autonomy limits in a regulated or enterprise environment.
• Exposure to multiple LLM providers and a clear point of view on when to use which.
• Prior work building reusable platform or infrastructure patterns that got adopted org-wide, not just within one team.

Why This Role

• Direct influence over how AI gets built across the company not one team's tool, but the standard everyone else builds on.
• A genuinely open architecture problem, not a maintenance job with a fixed answer key.
• Room to grow into the person others come to for how agentic AI should be done here.

Best Regards

Kyle,

Sr. US IT Recruiter

Infinity Tech Group Inc,

12 N Route 17 Suite # 201 Paramus NJ 07652

Kyle K At Infigroup Dotcom