> Markdown version of [/jobs/ext/4009435-genai-architect](https://www.wearedevelopers.com/jobs/ext/4009435-genai-architect). 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). --- # GenAI Architect - **Company:** Pyramid Consulting Inc. - **Location:** Columbus, OH, United States - **Experience:** Expert - **Salary:** $124,800.0 - $128,960.0 - **Contract:** Temporary contract - **Skills:** LangGraph Framework, Artificial Intelligence, Python (Programming Language), Azure Machine Learning, Systems Integration, Workflow Management Systems, Design of Telemetry/logging Agents, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Agentic-AI, AI Platforms - **Published:** October 29, 2026 - **Apply:** https://www.thejobnetwork.com/job/0b50ff8e-23dc-4fe0-a98f-b45e088f9a8d/genai-architect ## About the Role * 5+ years of strong experience architecting and implementing Agentic AI systems using LLMs, LangGraph, MCP, and RAG. * Expertise in Python, data ingestion/retrieval, vector databases, and AI application development. * Hands-on experience with Azure AI Foundry, Azure AI Services, or similar AI platforms. * Deep understanding of observability, governance, reliability, workflow orchestration, and context/memory engineering. * Healthcare industry experience is highly preferred. ## Description Immediate need for a talented GenAI Architect. This is a 06+months contract opportunity with long-term potential and is located in Columbus, OH(Onsite). Please review the job description below and contact me ASAP if you are interested., * Assess business processes, systems, and data landscapes to identify high-impact GenAI opportunities. * Design and own end-to-end AI solution architecture, including LLM selection, agent design, RAG frameworks, integrations, security, governance, and evaluation methodologies. * Lead hands-on implementation efforts and establish engineering and prompt-engineering best practices. * Collaborate with business, IT, security, and engineering teams to align objectives and manage delivery risks. * Drive successful deployment, adoption, and measurement of business outcomes through AI solutions.