AI Architect - Enterprise Integrations

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.

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.

• Architect end-to-end enterprise AI solutions that integrate AI models, data platforms, and enterprise systems into cohesive, production-grade architectures
• Define integration patterns across AI services, APIs, data pipelines, and core business systems to ensure interoperability and extensibility
• Translate complex business requirements into scalable AI-powered solution designs, with clear articulation of tradeoffs, risks, and value drivers
• Lead architecture design reviews and provide hands‑on guidance to delivery teams across active engagements
• Contribute to practice development by building reusable assets, frameworks, and point-of-views that strengthen our AI delivery capability

• Design and implement Azure-based AI platform infrastructure that supports scalable model deployment, data ingestion, and application integration
• Define infrastructure-as-code standards and CI/CD pipeline patterns for AI workloads, enabling repeatable and auditable deployments
• Architect cloud‑native environments optimized for AI throughput, cost efficiency, and operational resilience
• Establish platform engineering standards that enable development teams to build, test, and ship AI solutions faster and more reliably
• Evaluate and recommend emerging platform capabilities, cloud services, and tooling that advance our delivery approach

• Design observability frameworks for AI systems including model monitoring, prompt evaluation, drift detection, and performance alerting
• Define AI governance standards covering responsible AI principles, audit trails, explainability requirements, and human‑in‑the‑loop controls
• Establish development lifecycle practices for AI — from experimentation and model validation through to production deployment and ongoing operations
• Implement guardrail frameworks and safety controls for agentic and generative AI workloads to ensure appropriate oversight and auditability
• Champion MLOps and AI engineering best practices across the team, ensuring solutions are maintainable, observable, and continuously improvable

• Serve as a senior technical voice both internally and with clients, sharing expertise, identifying emerging patterns, and helping define our AI point of view
• Mentor…