Principal Cloud Engineer

ABOUT GREYSTARGreystar is a leading, fully integrated global real estate platform offering expertise in property management, investment management, development, and construction services in institutional-quality rental housing. Headquartered in Charleston, South Carolina, Greystar manages and operates over $300 billion of real estate in more than 265 markets globally with offices throughout North America, Europe, South America, and the Asia-Pacific region. Greystar is the largest operator of apartments in the United States, managing over one million units/beds globally. Across its platforms, Greystar has nearly $79 billion of assets under management, including over $35 billion of development assets and over $36.5 billion of regulatory assets under management. Greystar was founded by Bob Faith in 1993 to become a provider of world-class service in the rental residential real estate business. To learn more, visit www.greystar.com.JOB DESCRIPTION SUMMARYThe Principal Cloud Engineer is a senior technical leader who pairs architectural vision with hands-on engineering execution. You will design and build the reference architectures, patterns, and standards that support Greystar’s global operations, then implement those designs yourself using modern cloud practices. This is not a role that stops at diagrams. This is the role that proves out patterns through working POCs, then enables the platform team to operationalize and scale them. You will partner closely with the Data, Digital, and AI (D2AI) team, where much of Greystar’s active cloud development happens today, while keeping a broader, enterprise-wide perspective. Much of that work is AI and data intensive, so a core part of this role is building the cloud foundation that Greystar’s AI and ML workloads run on, from accelerated compute and model serving to the Databricks data plane that powers them. We are looking for someone who thinks in cloud concepts rather than being tied to any single provider. The ideal candidate understands foundational principles - IAM, virtual networking, DNS, load balancing, compute, and storage - and can translate those concepts fluidly across Azure, AWS, or any platform our growing portfolio demands. You approach technology decisions with a methodology-first mindset: evaluating trade-offs, aligning infrastructure choices with business objectives, and building frameworks that scale across a complex, multi-entity organization. This is an individual contributor role with a strong mentoring component. You will guide and elevate systems administrators and engineers across the team, helping them grow into more strategic thinkers themselves. In addition to your resume, all candidates are required to include a short video (2–5 min) demonstrating how you have used AI tools in your engineering workflow — code generation, debugging, architecture, documentation, or similar. We recommend recording with Loom (free) or uploading as an unlisted YouTube video. Please embed this link at the top of your resume. Applications without a video link will not be reviewed.JOB DESCRIPTION What You Will Do:Cloud Architecture and Engineering:Design and build reference architectures, design patterns, and technology standards that ensure consistency, security, and scalability across all environments, and contribute to technology roadmaps that align cloud direction with businessobjectivesand growth plans.Design, implement, and continuously improve Greystar’s private networking architecture, including hub-and-spoke topology, private endpoint strategy, DNS architecture, and network segmentation standards across all cloud environments.Design and build Greystar’s container platform, delivering reference patterns for AKS and containerized workloads that underpin near-term initiatives including MCP-based services and AI/ML model serving infrastructure.Design and implement cloud infrastructure solutions across multi-cloud environments (Azure, AWS), with an emphasis on reliability, security, and cost-efficiency.Design and implement the infrastructure patterns for AI workloads and the Databricks data plane that D2AI’s analytics and AI products depend on.Enablement for Application Development Teams:Partner closely with application development teams - including the Data, Digital, and AI (D2AI) team - to help them move fast and safe by providing the patterns, guardrails, and platform capabilities they need to ship confidently.Build and curate paved-road solutions: reference implementations,Terraformmodules, pipeline templates, and starter architectures that let product teams adopt cloud services without reinventing the wheel.Remove friction byanticipatingcommon needs - networking, identity, secrets, deployment, observability - and delivering self-service capabilities that scale across teams.Serve as a trusted technical advisor on cloud design reviews, helping development teams choose the right services and patterns for their workloads.Infrastructure as Code and Auto