Principal AI Cloud Architect – Azure Cloud

Harris Computer; Missouri; Remote; USD 140,000 - 170,000; Full time

Job summary

Harris Computer is seeking a seasoned Principal AI Cloud Architect to lead the shift of our Cloud business unit to an AI-first operating model. This role will build and lead a small team of engineers focused on designing, deploying, and running AI agents that manage, monitor, and optimize our Cloud infrastructure in Microsoft Azure.

The ideal candidate has deep Azure expertise and hands-on experience with data platforms like Databricks, cloud networking, IAM, and FinOps.

Qualifications

• Extensive experience designing Azure-based AI production systems.
• Strong cross-functional leadership and client-facing skills.
• Proven ability to implement IaC with CI/CD integration.
• Hands-on with Databricks and data platforms.

Responsibilities

• Define AI strategy and roadmap for the Cloud unit.
• Lead a small team of AI and Cloud engineers.
• Architect multi-agent AI systems for AIOps.
• Design IaC patterns with Terraform and Bicep.
• Ensure security, governance, and compliance.
• Collaborate with stakeholders to deliver enterprise solutions.

Skills

Azure expertise

AI/ML implementation

Leadership

Client engagement

AI governance

Tools

Terraform

Bicep

Azure Databricks

Job description

Job Title

Principal AI Cloud Architect - Azure Cloud

Location

US (Remote)

Employment Type

Full-time

Job Description

We are seeking a seasoned Principal AI Cloud Architect to lead the shift of our Cloud business unit to an AI-first operating model. This role will build and lead a small team of engineers focused on designing, deploying, and running AI agents that manage, monitor, and optimize our Cloud infrastructure in Microsoft Azure. It is also client-facing. You will help clients adopt AI-driven Cloud operations and work closely with development teams to deliver enterprise-grade solutions.

The ideal candidate is an expert in Azure architecture with hands-on experience building production agentic AI systems. They also bring deep knowledge of data platforms (including Databricks), Cloud networking, identity and access management, and operational excellence. They will set the AI strategy for the Cloud business unit and turn it into working agents that reduce manual effort, improve reliability, and keep Cloud environments secure, compliant, and cost-effective.

Key Responsibilities

• Define and drive the AI strategy and roadmap for the Cloud business unit, 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 AI agents in production
• Architect multi-agent systems for AIOps, including anomaly detection, event correlation, ITSM ticket triage, and self-healing runbooks that reduce mean time to detect (MTTD) and mean time to resolve (MTTR)
• Lead the design of agents that generate, review, and validate Infrastructure as Code (Terraform, Bicep), with policy checks and automated validation built into CI/CD pipelines before changes reach production
• Develop FinOps agents that identify cost anomalies, rightsizing opportunities, and idle resources, and act on them within defined guardrails
• Design security and compliance agents for posture assessment, configuration drift detection, and automated collection of audit evidence
• Establish AI governance for agent operations, including human-in-the-loop approvals, access controls, guardrails, audit logging, and responsible AI practices suited to 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 the data foundations that support AI workloads
• Drive operational excellence, including monitoring, logging, observability, resiliency, and disaster recovery, for both Cloud platforms and the agents that run on them
• 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 keep improving the organization’s Cloud and AI capabilities and innovation roadmap

Required Qualifications

• 15+ years of experience in IT, with at least 10 years focused on Cloud architecture (Azure preferred)
• 3+ years of hands-on experience with AI/ML, 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 (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 (data lakes, ETL/ELT, streaming, lakehouse)
• Strong communication and presentation skills, with the ability to influence both technical and executive stakeholders

Preferred Qualifications

• 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

Core Competencies

• Excellent communication skills with the ability to explain complex technical and AI concepts to both technical and non-technical audiences
• Ability to provide clear and concise status reports against roadmap and overall adoption strategy
• Strong leadership skills, with the ability to build a team, set clear direction, and develop people
• Strong collaboration skills and ability to work effectively with clients, stakeholders, and cross-functional teams
• Client-focused mindset with the ability to build trusted relationships and deliver solutions aligned to business goals
• Strong analytical and problem-solving skills with the ability to make sound decisions in complex environments
• Pragmatic approach to AI adoption, balancing innovation with security, reliability, and risk
• Highly organized and results-driven, with the ability to manage multiple priorities and meet deadlines
• Commitment to quality, operational excellence, and continuous improvement

Travel

Up to 20% travel may be required for client meetings, project work, or team collaboration

Our company complies with all local/state regulations in regard to displaying salary ranges. If required, the salary range(s) are displayed below and are specifically for those potential hires who will perform work in or reside in the location(s) listed, if selected for the role. Any offered salary is determined based on internal equity, internal salary ranges, market data, ranges, applicant's skills and prior relevant experience, certain degrees and certifications (e.g. JD, technology), for example.

Salary range

$140,000 - $170,000 USD. The salary range reflects the anticipated base salary for this position at the time of posting. Final compensation may vary based on factors including experience, skills, education