Introduction
A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. Youâ€™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, youâ€™ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. Youâ€™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 Responsibilities
Enterprise AI Solution Architecture
<ul>
<li>Architect end-to-end enterprise AI solutions that integrate AI models, data platforms, and enterprise systems into cohesive, production-grade architectures</li>
<li>Define integration patterns across AI services, APIs, data pipelines, and core business systems to ensure interoperability and extensibility</li>
<li>Translate complex business requirements into scalable AI-powered solution designs, with clear articulation of tradeoffs, risks, and value drivers</li>
<li>Lead architecture design reviews and provide hands-on guidance to delivery teams across active engagements</li>
<li>Contribute to practice development by building reusable assets, frameworks, and point-of-views that strengthen our AI delivery capability</li>
</ul>
Platform Engineering &amp; Cloud Infrastructure
<ul>
<li>Design and implement Azure-based AI platform infrastructure that supports scalable model deployment, data ingestion, and application integration</li>
<li>Define infrastructure-as-code standards and CI/CD pipeline patterns for AI workloads, enabling repeatable and auditable deployments</li>
<li>Architect cloud-native environments optimized for AI throughput, cost efficiency, and operational resilience</li>
<li>Establish platform engineering standards that enable development teams to build, test, and ship AI solutions faster and more reliably</li>
<li>Evaluate and recommend emerging platform capabilities, cloud services, and tooling that advance our delivery approach</li>
</ul>
Observability,
Governance &amp; Development Lifecycle
<ul>
<li>Design observability frameworks for AI systems including model monitoring, prompt evaluation, drift detection, and performance alerting</li>
<li>Define AI governance standards covering responsible AI principles, audit trails, explainability requirements, and human-in-the-loop controls</li>
<li>Establish development lifecycle practices for AI — from experimentation and model validation through to production deployment and ongoing operations</li>
<li>Implement guardrail frameworks and safety controls for agentic and generative AI workloads to ensure appropriate oversight and auditability</li>
<li>Champion MLOps and AI engineering best practices across the team, ensuring solutions are maintainable, observable, and continuously improvable</li>
</ul>
Thought Leadership &amp; Practice Growth
<ul>
<li>Serve as a senior technical voice both internally and with clients, sharing expertise, identifying emerging patterns, and helping define our AI point of view</li>
<li>Mentor architects and engineers on platform engineering, governance, and AI architecture best practices</li>
<li>Engage in pre-sales and solutioning activities, helping shape proposals and articulate our technical differentiation</li>
</ul>
This role can be performed from anywhere in the US.
Required Technical And Professional Expertise
<ul>
<li>8+ years of experience in enterprise architecture, with demonstrated expertise spanning AI/ML, cloud infrastructure, and systems integration</li>
<li>Hands-on experience designing enterprise AI solutions on Azure, including Azure OpenAI, Azure Machine Learning, and supporting data services</li>
<li>Strong grounding in platform engineering, infrastructure-as-code (e.g., Terraform, Bicep), and CI/CD pipeline design for AI workloads</li>
<li>Experience building observability and monitoring solutions for AI/ML systems in production environments</li>
<li>Proven ability to define and enforce AI governance, responsible AI, and compliance frameworks at enterprise scale</li>
<li>Comfortable leading design conversations with both technical teams and client stakeholders</li>
</ul>
Preferred Technical And Professional Experience
<ul>
<li>Familiarity with agentic AI architectures, orchestration frameworks (LangChain, Semantic Kernel, AutoGen), and RAG pipeline design</li>
<li>Experience with Azure data platform services including Microsoft Fabric, Azure Synapse Analytics, and Azure Data Factory</li>
<li>Knowledge of MLOps practices including model versioning, A/B testing, canary deployments, and feedback loop design</li>
<li>Background contributing to a consulting practice or Center of Excellence — building frameworks, POVs, and reusable assets</li>
<li>Azure certifications such as Azure Solutions Architect Expert, Azure AI Engineer Associate, or DevOps Engineer Expert</li>
</ul>

AI Architect - Enterprise Integrations

AI Architect - Enterprise Integrations

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