Senior AI Solution Architect
Role Overview
A 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.
Responsibilities
Set the architectural vision and direction for AI engagements, establishing design standards and reusable patterns that elevate the quality and speed of delivery.
Lead architecture design workshops and strategy sessions with client stakeholders, including executive and technical audiences.
Serve as a trusted advisor to clients on Azure AI capabilities, use case prioritization, and technology roadmap development.
Mentor delivery team members and contribute to practice development through knowledge sharing and asset creation.
Define and govern complete Azure AI architectures spanning Azure OpenAI Service, Azure Machine Learning, and enterprise data platforms.
Design solutions that are scalable, secure, cost-optimized, and aligned to enterprise architecture standards from inception.
Map AI use cases to measurable business value, ensuring that prioritization decisions are grounded in ROI and strategic fit.
Create reference architectures, integration patterns, and technical blueprints that accelerate delivery across the engagement.
Embed responsible AI practices, data governance, and compliance requirements into every architectural decision.
Define guardrails, monitoring standards, and audit frameworks to ensure AI solutions are observable, trustworthy, and maintainable at scale.
Establish operating model standards for AI deployment, support, and lifecycle management across the platform.
Engage directly and continuously with client stakeholders, translating complex technical architecture into clear business terms.
Collaborate across data engineering, application, and business teams to drive seamless end-to-end delivery.
Identify and manage technical risks proactively, surfacing tradeoffs and recommended mitigations clearly and early.
Requirements
8+ years of experience in enterprise or solution architecture, with 3+ years focused on AI/ML solutions.
Deep, hands-on expertise with Azure AI services including Azure OpenAI Service, Azure Machine Learning, and Azure AI Studio.
Proven track record defining and governing end-to-end AI architectures at enterprise scale.
Strong grounding in enterprise data platforms, cloud-native design principles, and integration architecture.
Experience in a client-facing consulting or professional services environment with direct executive stakeholder engagement.
Excellent communication and facilitation skills — able to lead design sessions and present recommendations with confidence.
Preferred Skills
Experience with agentic AI frameworks (LangChain, AutoGen, Semantic Kernel) and RAG pipeline design.
Familiarity with Azure data services including Microsoft Fabric, Azure Synapse Analytics, and Azure Data Factory.
Knowledge of AI governance frameworks, responsible AI principles, and enterprise risk management practices.
Azure certifications such as Azure Solutions Architect Expert or Azure AI Engineer Associate.