Data & Analytics Senior AI Engineer - Agentic Systems Professional Multiple Cities

About the Role We are seeking a skilled AI Engineer to join an active enterprise AI engagement in a hands‑on, client‑facing capacity. This is a senior individual contributor role requiring deep technical proficiency in Agentic AI — you will be expected to operate independently, interact directly with the client, and deliver with minimal oversight. You will be responsible for building, fine‑tuning, and operationalizing AI solutions on Azure, with a specific focus on agentic workflows, prompt engineering, RAG pipelines, and production‑grade model deployment. The client expects a high‑caliber engineer who can perform from day one. What You'll Do Agentic AI Development Design, build, and deploy agentic AI workflows and multi‑agent systems using Azure OpenAI and supporting frameworks. Develop and optimize prompt engineering strategies to maximize model performance and reliability. Build and maintain Retrieval‑Augmented Generation (RAG) pipelines that enable grounded, context‑aware AI responses. Implement agent orchestration patterns including tool calling, memory management, and human‑in‑the‑loop workflows. Client Engagement & Collaboration Engage directly with client stakeholders to gather requirements, demo capabilities, and walk through technical solutions. Communicate clearly on progress, blockers, and technical tradeoffs — no hand‑holding required. Collaborate with architects, data engineers, and business teams to ensure seamless end‑to‑end integration. Engineering & Operationalization Deploy and manage AI models using Azure ML, Azure AI Studio, or equivalent Azure services. Integrate AI capabilities into enterprise applications via APIs, event‑driven pipelines, and microservices. Establish monitoring, evaluation, and feedback loops to ensure ongoing model performance and reliability in production. Ensure solutions meet enterprise standards for security, scalability, and compliance. Required Qualifications Bachelor's Degree in a relevant field. 7+ years designing, developing, and deploying scalable AI applications leveraging LLMs, RAG architectures, and agentic AI workflows. Experience building and operationalizing AI orchestration pipelines using frameworks such as LangChain and LangGraph. Ability to develop AI agents capable of tool calling, contextual retrieval, memory/state management, multi‑agent coordination, and autonomous workflow execution. Experience implementing MCP (Model Context Protocol) integration patterns for secure, modular interoperability between AI agents, enterprise systems, tools, and data sources. Support industrialization of AI capabilities through reusable architecture patterns, standardized deployment frameworks, monitoring, testing, evaluation pipelines, and operational support models. Develop and integrate enterprise‑grade APIs, vector databases, workflow platforms, and operational systems into AI‑enabled business processes. Implement AI governance, security, logging, guardrails, and human‑in‑the‑loop controls to support responsible and scalable AI adoption. Contribute to CI/CD, LLMOps/MLOps, and cloud‑native deployment practices supporting enterprise‑scale AI delivery. Preferred Skills Experience with agentic frameworks such as LangChain, LangGraph, AutoGen, Semantic Kernel, or CrewAI. Familiarity with vector databases (e.g., Azure AI Search, Pinecone, Weaviate) for RAG implementations. Knowledge of MLOps practices and CI/CD pipelines for AI model deployment and lifecycle management. Experience with enterprise integration patterns and connecting AI solutions to CRMs, ERPs, or data platforms. Benefits Healthcare benefits including medical and prescription drug coverage, dental, vision, and mental health & well‑being. Financial programs such as 401(k), cash‑balance pension plan, the IBM Employee Stock Purchase Plan, financial counseling, life insurance, short‑ and long‑term disability coverage, and opportunities for performance‑based salary incentive programs. Generous paid time off including 12 holidays, minimum 56 hours sick time, 120 hours vacation, 12 weeks parental bonding leave in accordance with IBM policy, and other Paid Care Leave programs. Training and educational resources on a personalized, AI‑driven learning platform where IBMers can grow skills and obtain industry‑recognized certifications. Diverse and inclusive employee resource groups, giving and volunteer opportunities, and discounts on retail products, services, and experiences. Equal‑Opportunity Employment IBM is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by the applicable law. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status. We consider qualified applicants with criminal histories, consistent with applicable law. #J-18808-Ljbffr