> Markdown version of [/jobs/ext/3065746-cloud-ai-architect-agentic-ai](https://www.wearedevelopers.com/jobs/ext/3065746-cloud-ai-architect-agentic-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud/AI Architect Agentic AI - **Company:** Infinity Tech Group Inc - **Location:** Stamford, CT, United States - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Amazon Web Services, Audit Trail, Cloud Computing, Cloud Engineering, Information Engineering, Search Technologies, AI Infrastructure, Google Cloud, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, AI Platforms, Virtual Agents - **Published:** September 25, 2026 - **Apply:** https://www.dice.com/job-detail/aea46a5b-1aaa-4fa2-9047-344b60b6aee6 ## About the Role Experience designing and implementing Agentic AI / Autonomous AI systems Strong experience with AWS and/or Google Cloud Platform cloud architecture Hands-on experience with RAG architecture and enterprise knowledge retrieval Experience with LLMs, prompt engineering, embeddings, vector databases, and AI orchestration Experience with LangChain / LangGraph / CrewAI / Bedrock Agents / Vertex AI or equivalent frameworks Experience designing enterprise AI infrastructure covering security, networking, compute, storage, scalability, and cost optimization Experience establishing Agentic AI governance frameworks, including guardrails, audit trails, autonomy limits, and responsible AI controls Exposure to multiple LLM providers and the ability to determine which model/provider is appropriate for different use cases Experience building reusable AI platforms, infrastructure patterns, or architecture frameworks adopted across multiple teams Strong stakeholder management, communication, architecture, and technical leadership skills ## Description This role will focus on architecting scalable AI solutions using AWS Agent Core, Google Cloud Platform Vertex AI, and other cloud-native AI services., Architect and implement Agentic AI pipelines involving multi-step reasoning, tool usage, orchestration, and autonomous workflows. Build enterprise-grade RAG (Retrieval-Augmented Generation) systems, including data ingestion, chunking strategies, embedding pipelines, vector stores, and retrieval optimization. Define cloud architecture patterns for AI workloads covering compute, storage, networking, security, scalability, and cost optimization. Evaluate and select LLM providers, AI orchestration frameworks, and vector databases based on enterprise requirements. Work with technologies/frameworks such as AWS Agent Core, Google Cloud Platform Vertex AI, LangChain, LangGraph, CrewAI, Bedrock Agents, and equivalent platforms. Work with vector databases and search technologies such as OpenSearch, Pinecone, pgvector, or equivalent solutions. Collaborate with Data Engineering, Security, Cloud, Platform, and Engineering teams to ensure enterprise AI solutions meet scalability, reliability, security, and compliance standards. Develop reusable architecture blueprints, reference architectures, and implementations for Agentic AI and RAG use cases. Provide technical leadership and mentorship to engineering teams implementing AI solutions. Evaluate emerging cloud AI services and recommend adoption where they provide measurable business value. Translate business requirements into scalable, secure, and production-ready AI architectures.