Senior Level Principal Cloud Architect Jobs
Senior level principal cloud architect jobs place experienced professionals in charge of cloud strategy, platform direction, and the cross-functional teams and initiatives that bring enterprise architecture to life. Roles cover 86% remote and hybrid settings across Insurance, Technology & Software, and Manufacturing, with employers like CVS Health, Symbotic, and Altera Digital Health hiring at this level now.
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Job Title: Principal AI Cloud Architect – Azure Cloud
Location: US (Remote)
Employment Type: Full-time
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.
Job Title: Principal AI Cloud Architect – Azure Cloud
Location: US (Remote)
Employment Type: Full-time
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.
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Senior Level Principal Cloud Architect Jobs: Frequently Asked Questions
How do I get a senior level principal cloud architect job?
Employers at this level look for candidates who have owned end-to-end cloud architecture decisions, not just contributed to them. Demonstrating that you have set technical direction, driven platform-wide migrations or modernization programs, and mentored engineering teams gives you an edge. A strong portfolio of outcomes, including cost optimization wins and reliability improvements at scale, signals readiness for a senior principal role.
Which companies hire senior level principal cloud architects?
Companies hiring senior level principal cloud architects right now include CVS Health, Symbotic, and Altera Digital Health, based on current listings on Migrate Mate as of November 2026. At this level, hiring tends to come from large enterprises, cloud-native technology firms, and consultancies that need architects capable of owning strategy across complex, multi-cloud environments.
Are there remote senior level principal cloud architect jobs?
Yes, remote and hybrid options are common at this level, though some roles require on-site presence for executive collaboration or regulated-industry compliance. About 86% of senior level principal cloud architect openings are remote or hybrid as of November 2026, reflecting how broadly organizations have accepted distributed work for senior technical leadership.
What makes a principal cloud architect role senior level?
Senior level principal cloud architect roles are defined by scope, autonomy, and influence. Where mid-level architects execute within defined frameworks, senior principals set those frameworks, evaluate emerging technologies for adoption, and drive decisions that affect the entire organization. They also carry explicit responsibility for mentoring architects and engineers, and they engage directly with executive stakeholders on cloud investment and risk.
Which industries hire the most senior level principal cloud architects?
Senior Level principal cloud architect roles concentrate in Insurance, Technology & Software, and Manufacturing, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they operate at a scale and regulatory complexity that requires experienced architects who can govern multi-cloud platforms, manage vendor strategy, and lead large engineering organizations through continuous modernization.