Sr Cloud Engineer

Marriott Vacations Worldwide

About The Position

The Senior Cloud Engineer is responsible for designing, implementing, and supporting scalable automation and platform engineering capabilities that enable MVW’s global technology environment. This role develops and maintains infrastructure and platform services as code across MVW’s multi-cloud ecosystem, including Amazon Web Services (primary), Microsoft Azure, and Oracle Cloud Infrastructure, while supporting the container, data, and integration platforms that operate within those environments, such as Red Hat OpenShift Service on AWS (ROSA), Oracle Autonomous Data Warehouse (ADW), and Microsoft Fabric. Working as a subject matter expert within Global Technology, the incumbent partners with infrastructure, security, application, data, and business teams to deliver reliable, secure, and cost-effective cloud solutions. The role applies automation, AI-enabled engineering practices, and disciplined governance to reduce operational complexity, improve self-service capabilities, strengthen platform reliability, and accelerate technology delivery in alignment with MVW’s security, compliance, and AI governance standards.

Requirements

BA/BS in Computer Science, Computer Engineering, Information Systems, or a related technical discipline preferred; equivalent hands-on professional experience accepted in lieu of a degree.
Associate or Professional Level AWS or Azur
CKA/CKAD or EX280
Terraform Associate or a vendor AI/ML certification
7+ years in an IT engineering, administration, or architecture role, including 5+ years of hands-on automation and infrastructure as code.
4+ years designing and operating production workloads in at least one major public cloud (AWS or Azure preferred), working exposure to a second (OCI).
3+ years supporting production Kubernetes, with OpenShift or ROSA strongly preferred
3+ years writing production-grade code in Python (preferred) or a comparable language
Automating large-scale, multi-environment infrastructure estates; enterprise application deployment, maintenance, and administration; production support including occasional on-call participation; and infrastructure as code and configuration management in a regulated or audited enterprise environment.
Solves systemic problems through automation rather than addressing issues ticket by ticket.
Troubleshoots systematically and exercises sound judgment under pressure.
Weighs trade-offs across cost, reliability, security, and speed and explains the rationale clearly.
Uses Terraform and Ansible at a module and collection authoring level.
Applies knowledge of Kubernetes and OpenShift workloads, operators, networking, storage, RBAC, and admission control.
Supports GitOps and continuous delivery using Argo CD, Helm, Kustomize, Tekton, and/or Azure DevOps pipelines.
Demonstrates cloud and platform fundamentals, including networking, identity and federation, secrets management, key management, Linux, Windows Server, VMware, REST APIs, provider SDKs, observability, and SLO practices.
Applies AI working knowledge of AI/LLM concepts, including prompting, context management, retrieval, tool calling, evaluation, and token/cost awareness.
Organizes work across priorities, timelines, dependencies, and competing demands.
Supports planning and delivery by clarifying scope, identifying risks, and driving assigned work to completion.
Communicates complex technical concepts clearly to engineers and non-technical stakeholders, both verbally and in writing.
Builds trust across Global Technology, business partners, vendors, and cross-functional teams.
Gives and receives direct feedback constructively.
Demonstrates strong presentation and diagramming skills.
Operates effectively with ambiguity and limited oversight.
Stays current with a fast-moving technology landscape.

Nice To Haves

Multi-cloud operations spanning AWS, Azure, and OCI rather than a single provider, and managed OpenShift (ROSA or ARO) at scale including cluster upgrades and day-2 operations.
Oracle ADW, Microsoft Fabric, or comparable managed data platforms; platform engineering or internal developer platform work (Backstage or equivalent); hospitality, timeshare, travel, or another distributed multi-site enterprise environment.
Hands-on use of AI coding assistants and agentic development tools (Claude Code, GitHub Copilot) in a team setting, including the review and testing practices that make AI-generated code safe to ship.
Building services or internal tooling against LLM APIs (Anthropic Claude, Azure AI Foundry, Amazon Bedrock), including prompt design, structured outputs, and tool calling.
Evaluation and lifecycle discipline for AI systems: eval harnesses, prompt and model versioning, and drift monitoring.
AIOps and AI governance: LLM-assisted incident triage, data classification, acceptable use, audit evidence, and cost control.

Responsibilities

Design, build, and operate multi-cloud infrastructure as code across AWS, Azure, and OCI using Terraform and Ansible, authoring, versioning, and testing reusable modules and collections rather than only consuming them.
Automate landing zone, network, identity, and workload provisioning across dozens of environments from a single, auditable control plane, and enforce guardrails through policy as code (AWS SCPs, Azure Policy, OPA) so that compliance applies at deploy time rather than after the fact. Partner with Network and Information Security on private connectivity, transit architectures, and zero-trust segmentation (e.g., Illumio).
Operate, upgrade, and extend production Kubernetes and OpenShift (ROSA) clusters at enterprise scale, including cluster lifecycle automation, drift detection, and progressive delivery patterns.
Maintain GitOps-based delivery with Argo CD, Helm, and Kustomize, managing code and configuration in Bitbucket (preferred) or GitHub with a defined branching strategy, pull request review, and release tagging; build golden paths and self-service capabilities, and advise application teams on containerization, workload placement, and resource governance.
Automate provisioning and operations for Oracle Autonomous Data Warehouse (connectivity, wallet and secret management, scaling, backup posture), and support Confluent Kafka and MuleSoft CloudHub 2.0 with infrastructure, networking, and deployment automation.
Work with Data & Analytics partners to make environment promotion for data and analytics artifacts as repeatable as application delivery using IaC.
Instrument platforms with metrics, logs, and traces; define SLOs and actionable alerting, drive down alert noise, contribute to incident response and blameless postmortems, and automate remediation of recurring failure modes.
Deliver cost visibility and optimization: tagging and showback, rightsizing, commitment management (Reserved Instances / Savings Plans), storage lifecycle policy, and capacity planning across cloud and data platforms.
Serve as a subject matter expert alongside business, application, and infrastructure teams; gather requirements, estimate effort from inception to delivery, and complete work within scope, priority, timeline, and budget, running smaller efforts independently and contributing to larger programs with limited oversight.
Produce design specifications, architecture diagrams, and operational runbooks and keep them current; mentor less experienced engineers, conduct design and code reviews, manage vendor escalations and product evaluations, and sustain a culture of quality, innovation, and disciplined experimentation.