Senior AI Architect - Enterprise Integrations
IntroductionA career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.Your Role And ResponsibilitiesAbout the RoleWe are seeking a Senior AI Architect – Enterprise Integrations to join our growing AI practice. As demand for intelligent, connected enterprise solutions accelerates, we are building out a specialized capability in AI-native architecture and agentic system design. This is a senior, client-facing role where you will provide thought leadership, shape practice offerings, and lead delivery on high-impact AI integration engagements.You will be the subject matter expert at the intersection of AI agents and enterprise systems — designing and building the connective tissue that makes AI solutions work in the real world.What You'll DoThought Leadership & Practice DevelopmentServe as an internal champion for AI integration architecture strategy, helping to define and grow this capability within the firmDevelop points of view, reference architectures, and reusable assets that accelerate client deliveryMentor and upskill other architects and consultants on AI integration patterns and emerging standardsClient Engagement & Solution ArchitectureLead discovery, design, and architecture sessions with clients to define AI integration strategiesTranslate complex business requirements into scalable, secure, and maintainable AI-powered solutionsProvide cloud and LLM consumption cost estimates, optimizing for cost-effective architecture through fit-for-purpose model selection, efficient prompting & caching, and scalable infrastructure designPresent architectural recommendations to executive and technical stakeholders with clarity and confidenceLead cross-functional development teams to deliver enterprise-grade, production-ready AI solutions, ensuring alignment to architecture standards, scalability, and operational excellenceTechnical DeliveryArchitect and implement integrations between AI agents and enterprise systems including CRMs, ERPs, data platforms, and third-party APIsEstablish a semantic data layer that standardizes and contextualizes enterprise data, enabling AI agents to reliably discover, interpret, and interact with systems & dataDefine patterns for agent orchestration, tool calling, memory management, and human-in-the-loop workflowsDesign and build Model Context Protocol (MCP) gateway & servers that expose enterprise data, tools, and APIs as structured context for AI agentsEnsure solutions meet enterprise standards for security, observability, and reliabilityThis role can be performed from anywhere in the US.Preferred EducationMaster's DegreeRequired Technical And Professional ExpertiseWhat You BringRequired Skills & Experience8+ years of experience in application or solution architecture, with at least 2+ years focused on AI/ML systemsHands-on experience designing and building MCP (Model Context Protocol) serversProven experience integrating AI agents with enterprise systems and workflowsDeep understanding of agentic AI frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, or similar)Strong knowledge of API design (REST, GraphQL), event-driven architecture, and enterprise integration patternsExperience working with LLM providers (OpenAI, Anthropic, Azure, IBM, AWS, Google, etc.) and their APIsProficiency in Python and/or TypeScript/JavaScript for building AI integration solutionsConsulting or professional services experience — comfortable owning client relationships and leading engagementsPreferred SkillsPreferred technical and professional experienceFamiliarity with cloud platforms (Azure, AWS, or GCP) and cloud-native deployment patternsExperience with RAG (Retrieval-Augmented Generation) architectures and vector databasesBackground in enterprise middleware or iPaaS platforms (MuleSoft, Boomi, Azure Integration Services)Knowledge of AI security considerations including prompt injection, data governance, and access controls