Senior AI Solution Architect
Indexed description
Your Role And Responsibilities
Thought Leadership & Technical Direction
- 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
- Develop 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
- Ensure alignment with enterprise security posture including identity, access management, data residency, and regulatory requirements
- 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
Required Technical And Professional Expertise
Required Skills & Experience
- 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
- 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
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