AI Prompt Engineer / Agentic AI Engineer

AI Prompt Engineer / Agentic AI Engineer (3 ON, 3 Off) Role Summary - Role Type: Client-facing, hands-on engineering + solutioning (pre-sales through early delivery)  - Location: Major US hub (e.g., New York, Bay Area, Dallas, Chicago – flexible for the right candidate). Travel Expected.   - Level: Manager/Principal/Senior Principal  - Business Unit:  (Enterprise AI Platforms & Agentic Solutions).   - Reporting to: Artificial Intelligence Leader, North America.  About Company: Role  summary   The resource will support the design, development, and delivery of Agentic AI solutions by creating, optimizing, and managing AI prompts, agent workflows, and MCP-integrated tools. The role will focus on enabling intelligent AI agents capable of autonomous reasoning, task orchestration, tool utilization, and workflow execution across enterprise applications. Key Responsibilities - Design, develop, and optimize prompts for Large Language Models (LLMs) to improve accuracy, reliability, and business outcomes. - Build and configure Agentic AI solutions that leverage planning, reasoning, memory, and multi-step task execution capabilities. - Develop and integrate MCP (Model Context Protocol) tools, enabling AIagents to securely discover and interact with enterprise systems, APIs, and data sources. - Design agent architectures, tool-calling frameworks, retrieval mechanisms, and context management strategies. - Collaborate with product managers, architects, and engineering teams to translate business requirements into AI-driven solutions. - Implement Retrieval-Augmented Generation (RAG), knowledge grounding, and context orchestration patterns. - Define evaluation frameworks and prompt testing methodologies to measure agent performance, quality, and reliability. - Ensure AI solutions adhere to security, compliance, governance, and responsible AI standards. - Support deployment, monitoring, troubleshooting, and continuous improvement of AI agents and MCP-enabled workflows. - Contribute to architecture reviews, technical design documentation, and engineering best practices for AI platforms.Required Skill - Experience with Large Language Models (OpenAI, Azure OpenAI, Anthropic, Gemini, or equivalent). - Strong understanding of prompt engineering, AI agent frameworks, and conversational AI systems. - Experience building Agentic AI applications using Semantic Kernel, LangChain, LangGraph, AutoGen, CrewAI, or similar frameworks. - Hands-on experience with MCP servers, tool integration, API orchestration, and enterprise system connectivity. - Proficiency in Python, TypeScript, or similar programming languages. - Familiarity with RAG architectures, vector databases, embeddings, and knowledge retrieval systems. - Understanding of cloud platforms such as Azure AI Foundry, Azure OpenAI, AWS Bedrock, or Google Vertex AI. - Strong problem-solving, analytical, and collaboration skills.Preferred Qualifications - Experience building enterprise copilots, AI assistants, or autonomous agent ecosystems. - Knowledge of AI governance, responsible AI, and security best practices. - Experience integrating AI agents with healthcare, health records, or regulated industry systems All your information will be kept confidential according to EEO guidelines.