Location:

Stamford, CT Employment Type:

Contract Experience Required:

15+

Years Work Location:

Stamford, CT Job Description We are seeking a highly experienced Enterprise / Principal Agentic AI Architect for a contract position in Stamford, CT, to lead enterprise-wide Agentic AI strategy, architecture, and transformation initiatives. The ideal candidate will have 15+ years of IT experience, with strong expertise in Generative AI, Large Language Models (LLMs), autonomous AI agents, multi-agent orchestration, RAG architectures, and enterprise AI governance. This role requires strategic leadership, hands-on AI architecture experience, and the ability to collaborate with executive leadership and cross-functional teams. Key Responsibilities Enterprise AI Strategy & Governance Define enterprise Agentic AI vision, strategy, and technology roadmap. Identify high-value AI automation opportunities aligned with business objectives. Establish AI governance frameworks and operating models. Drive enterprise AI transformation initiatives. Collaborate with executives, product owners, and business stakeholders. Agentic AI Architecture & Development Design autonomous AI agents and multi-agent architectures. Architect enterprise AI copilots and intelligent assistants. Implement RAG, agent memory, planning, reasoning, and orchestration frameworks. Develop AI solutions using LangGraph, CrewAI, Semantic Kernel, and LLM platforms. Integrate AI agents with enterprise applications, APIs, and business workflows. Ensure AI solution scalability, reliability, security, and performance. Technical Leadership Lead enterprise AI architecture reviews and technical design discussions. Mentor AI engineers and solution architects. Establish AI architecture standards, security controls, and best practices. Evaluate emerging AI technologies and frameworks. Collaborate with engineering, DevOps, security, and business teams.

Required Technical Skills AI & Agents:

Agentic AI, Generative AI, OpenAI GPT, Claude, Gemini, LangGraph, CrewAI, Semantic Kernel, Multi-Agent Systems.

RAG & Knowledge Layer:

RAG, Azure AI Search, Pinecone, ChromaDB, Weaviate, Neo4j, Knowledge Graphs, Vector Databases.

Cloud Platforms:

Azure OpenAI, AWS Bedrock, Google Vertex AI.

Infrastructure:

Kubernetes, Docker.

Enterprise Integration:

Jira, Azure DevOps, GitHub, SharePoint, REST APIs.

Architecture & Governance:

Enterprise AI Strategy, AI Governance, AI Security, Agent Orchestration, AI Architecture. Required Qualifications Minimum 15+ years of IT experience , including enterprise architecture and technical leadership. Strong hands-on experience designing Agentic AI and multi-agent architectures. Proven experience implementing Generative AI, LLMs, RAG, and AI copilots. Strong knowledge of LangGraph, CrewAI, or Semantic Kernel. Experience with vector databases, embeddings, semantic search, and knowledge graphs. Experience designing secure, scalable, production-ready enterprise AI solutions. Excellent communication, leadership, and stakeholder management skills. Ability to work effectively with executive leadership and technical teams. Preferred Qualifications Enterprise AI transformation and roadmap development experience. Production implementation of multi-agent AI solutions. Knowledge of GraphRAG and advanced retrieval architectures. Experience with AI governance, responsible AI, and enterprise security standards. Strong multicloud architecture experience.