Principal AI Cloud Architect – Azure Cloud

Harris Computer•Remote - North Carolina, IN

3d•$140,000 - $170,000•Remote

About The Position

We are seeking a seasoned Principal AI Cloud Architect to lead the shift of the Cloud business unit to an AI-first operating model. The role builds and leads a small team of engineers designing, deploying, and operating AI agents that manage, monitor, and optimize Cloud infrastructure in Microsoft Azure. It is client-facing and involves helping clients adopt AI-driven Cloud operations while working closely with development teams to deliver enterprise-grade solutions. The successful candidate brings expert Azure architecture knowledge and hands-on experience building production agentic AI systems, alongside deep knowledge of data platforms such as Databricks, Cloud networking, identity and access management, and operational excellence. The role sets the AI strategy for the Cloud business unit and turns it into working agents that reduce manual effort, improve reliability, and keep Cloud environments secure, compliant, and cost-effective. The position may require up to 20% travel for client meetings, project work, or team collaboration.

Requirements

15+ years of experience in IT, with at least 10 years focused on Cloud architecture; Azure preferred.
At least 3 years of hands-on AI/ML experience, including at least 2 years building and deploying LLM-based or agentic AI solutions in production.
Experience leading and developing engineering teams, including hiring, coaching, and setting technical direction.
Hands-on experience with Azure AI Foundry, Azure OpenAI, and agent frameworks.
Working knowledge of agent design patterns, including tool use, multi-agent orchestration, retrieval-augmented generation (RAG), and Model Context Protocol (MCP).
Experience applying AI or automation to Cloud operations, such as AIOps, automated remediation, IaC generation, FinOps, or security posture management.
Proven track record of working directly with clients and cross-functional development teams to deliver enterprise solutions.
Deep expertise in Microsoft Azure services, including compute, storage, security, and platform services.
Hands-on experience with Azure Databricks and modern data architecture, including data lakes, ETL/ELT, streaming, and lakehouse.
Strong communication and presentation skills, with the ability to influence technical and executive stakeholders.
Ability to explain complex technical and AI concepts to technical and non-technical audiences and provide clear, concise status reports against roadmaps and adoption strategies.
Strong leadership, collaboration, client relationship, analytical, and problem-solving skills.
Pragmatic approach to AI adoption, balancing innovation with security, reliability, and risk.
Highly organized and results-driven, able to manage multiple priorities and meet deadlines.
Commitment to quality, operational excellence, and continuous improvement.

Nice To Haves

Experience with AWS or Google Cloud in addition to Azure.
Experience in healthcare or other regulated industries, including HIPAA and handling protected health information (PHI).
Familiarity with AI governance frameworks such as the NIST AI Risk Management Framework.
Experience with LLMOps practices, including agent evaluation, prompt and model versioning, and monitoring agent behavior in production.
Relevant certifications such as Azure Solutions Architect Expert or Azure AI Engineer Associate.

Responsibilities

Define and drive the Cloud business unit’s AI strategy and roadmap, moving infrastructure operations from manual and script-based processes to agent-driven automation.
Build, lead, and mentor a team of 2–6 AI and Cloud engineers responsible for designing, developing, and operating production AI agents.
Architect multi-agent AIOps systems for anomaly detection, event correlation, ITSM ticket triage, and self-healing runbooks to reduce MTTD and MTTR.
Lead the design of agents that generate, review, and validate Infrastructure as Code using Terraform and Bicep, with policy checks and automated validation in CI/CD pipelines before production.
Develop FinOps agents that identify cost anomalies, rightsizing opportunities, and idle resources and act within defined guardrails.
Design security and compliance agents for posture assessment, configuration drift detection, and automated audit-evidence collection.
Establish AI governance for agent operations, including human-in-the-loop approvals, access controls, guardrails, audit logging, and responsible AI practices suitable for a regulated healthcare environment.
Partner with business stakeholders, clients, and engineering teams to define and architect end-to-end Cloud and AI solutions aligned with strategic objectives.
Lead architecture for data and analytics platforms, including Azure Databricks and data foundations that support AI workloads.
Drive operational excellence, including monitoring, logging, observability, resiliency, and disaster recovery, for Cloud platforms and their agents.
Establish and promote architecture standards, reusable agent patterns, and reference architectures across the organization.
Translate complex technical concepts into clear business value for clients and executive stakeholders, including measurable outcomes from AI adoption.
Evaluate emerging AI technologies, frameworks, and models, and continually improve Cloud and AI capabilities and the innovation roadmap.