AI Prompt Engineer / Agentic AI Engineer

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).
Hybrid arrangements and travel: This remain hybrid opportunities in New York, the Bay Area, Dallas, or Chicago, with no fully remote option. Travel may be approximately 25%, when necessary.
Level: Manager/Principal/Senior Principal
Business Unit: Enterprise AI Platforms & Agentic Solutions
Reporting to: Artificial Intelligence Leader, North America

Company Overview:
Global technology consulting and digital solutions company that enables enterprises across industries to reimagine how they operate, compete, and grow. By combining deep domain knowledge, advanced engineering, and transformation expertise, delivers measurable business impact at scale.

Enterprise AI business unit, purpose built to help organizations move beyond pilots into scaled, product iongrade AI adoption, functional consulting, an AI Foundry, and agentic AI platforms to deliver integrated solutions that transform how work gets done across the enterprise.Operating across Banking, Insurance, Manufacturing, Retail/CPG, Energy & Utilities, Travel & Hospitality, HiTech, and Media,  works closely with industry GTM teams to create repeatable AI solutions, accelerators, and transformation programs aligned to real business outcomes.

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