Cloud DevOps Engineer

Mastronardi Produce pioneered the commercial greenhouse industry in North America, and we’re now the leading greenhouse vegetable company on the continent. Our award-winning, flavorful produce is packed under the SUNSET® brand and is available at leading grocery retailers across North America. Family owned for over 70 years, we pride ourselves on having the most flavorful products and the best people in the industry. We are constantly pushing boundaries to be a leader in fresh produce innovation. We seek individuals that demonstrate our PRIDE values (Passion, Respect, Innovation, Drive, Excellence) to help us fulfill our mission to inspire healthy living through WOW flavor experiences.

Our corporate office in Livonia, Michigan is currently seeking an DevOps Cloud Engineer to join our team! The Cloud/DevOps Automation Engineer owns the full lifecycle of Mastronardi's cloud infrastructure, DevOps practices, and AI platform operations — from provisioning and securing Azure infrastructure to deploying, integrating, monitoring, and scaling the automation and AI systems that increasingly run the business. This role sits at the intersection of traditional infrastructure engineering and applied AI operations. It covers infrastructure-as-code, CI/CD, containerization, networking, and observability across Azure, as well as the deployment, integration, monitoring, and scaling of AI platforms such as Azure AI Foundry, Make.com automation scenarios, and the agentic workflows built by the AI Enablement team. This is a hands‑on individual contributor role: the Automation Engineer writes code and scripts, configures infrastructure, deploys and operates AI systems, and runs all of it directly in production — providing critical redundancy for cloud and AI-platform work that currently depends on a single person, and building the operational backbone that lets Mastronardi scale its automation and AI investments safely.

Values:

To perform the job successfully, the incumbent’s behavior must be consistent with the PRIDE values expected of all Mastronardi Produce employees: be Passionate; have Respect; be Innovative; be Driven and strive for Excellence.

Primary Responsibilities:

• Deploy and manage Azure infrastructure (VMs, networking, storage, identity) using infrastructure-as-code (ARM/Bicep, Terraform, or equivalent) rather than manual configuration.
• Design, build, and maintain CI/CD pipelines (Azure DevOps, GitHub Actions, or equivalent) for infrastructure changes, automations, and AI platform deployments.
• Build and maintain containerized workloads (Docker) and, where applicable, orchestration (Kubernetes/AKS or Azure Container Apps) for infrastructure and AI services.
• Implement configuration management and patching practices to keep servers, VMs, and platform components current, consistent, and secure.
• Design and maintain networking, identity, and access controls (Microsoft Entra ID, RBAC, network security groups) for infrastructure and platform integrations.
• Build monitoring, logging, and alerting (Azure Monitor, Log Analytics, or equivalent) across infrastructure, automations, and AI systems so issues are caught before they affect the business.
• Own backup, disaster recovery, and business continuity procedures for infrastructure and automation/AI platforms under this role's care.
• Manage cloud cost and capacity planning, right‑sizing resources and identifying optimization opportunities.
• Participate in an on‑call/incident response rotation, performing root‑cause analysis and driving remediation for production issues.
• Cross‑train other Cloud Operations & Infrastructure team members to reduce single-person dependency across infrastructure, automation, and AI‑platform responsibilities.

AI Platform Operations & Automation

• Deploy, configure, and operate Azure AI Foundry agents, models, and endpoints, connecting them to the systems and data they need to run reliably in production.
• Build, maintain, and troubleshoot automation scenarios in Make.com (and comparable platforms) that connect business systems, data sources, and AI capabilities.
• Build and operate the infrastructure and integration layer that lets AI Enablement's agentic workflows execute reliably at scale — including queues, retries, and error handling for multi‑step AI processes.
• Implement observability specific to AI workloads — tracking latency, token usage/cost, and failure rates for LLM calls and agent runs — and alert on anomalies.
• Manage versioning and rollout of AI models, prompts, and agent configurations, coordinating with the AI Enablement team so changes deploy safely without breaking production integrations.
• Implement guardrails and access controls around AI platforms and agents to keep usage secure, auditable, and within approved scope.
• Build and maintain integrations and connectors between Power Automate, Make.com, APIs, and enterprise systems (ERP, WMS, data platforms) that AI-driven processes depend on.
• Support scaling of AI inference and automation workloads as usage grows, adjusting infrastructure and platform configuration to maintain performance.
• Partner with the AI Enablement team to take AI solutions from a working build to a reliably operated, monitored production integration.
• Evaluate and recommend new automation, orchestration, and AI infrastructure tooling as Mastronardi's AI and automation footprint expands.
• Delivery, Documentation & Governance
• Test infrastructure changes, automations, and AI deployments thoroughly before release, including functional testing, failure‑mode testing, and rollback planning.
• Maintain a library of reusable scripts, templates, and automation patterns to reduce single‑person dependency and speed up delivery of future changes.
• Create and maintain clear documentation for all infrastructure, automations, AI deployments, and operating procedures, so no single person is the only source of knowledge.
• Ensure all infrastructure, automations, and AI platform work align with IT governance, security, and compliance standards.
• Bachelor’s degree in computer science, information systems, or a related field.

Specific Knowledge, Skills and Abilities Required

• Microsoft Azure: deploying and managing VMs, networking, storage, and identity using infrastructure-as-code (ARM/Bicep, Terraform, or equivalent).
• CI/CD: building and maintaining pipelines (Azure DevOps, GitHub Actions, or equivalent) for infrastructure and application deployments.
• Containerization: hands‑on experience with Docker required; Kubernetes/AKS or Azure Container Apps is an asset.
• Scripting/programming experience (PowerShell, Python, or similar) for infrastructure automation and custom integrations.
• Networking and identity: experience with Microsoft Entra ID, RBAC, network security groups, and related access‑control practices.
• Monitoring and observability: experience with Azure Monitor, Log Analytics, Grafana, or equivalent for production infrastructure.
• Backup, disaster recovery, and patching practices for production infrastructure.
• Cloud cost management and optimization practices (Azure Cost Management or equivalent).
• SQL: ability to query, join, and filter data across relational databases.
• ERP or enterprise systems experience (Microsoft Dynamics NAV/365, SAP, or equivalent) is an asset
• AI & Automation Platforms
• Hands‑on experience with Make.com (or a comparable integration/automation platform such as Zapier or n8n), including building, debugging, and maintaining production scenarios.
• Experience deploying and operating AI platforms such as Azure AI Foundry — connecting agents and models to production systems and data.
• Understanding of agentic AI and multi‑step autonomous workflows, and how to operate and monitor them reliably in production.
• Familiarity with LLM observability concepts — tracking latency, token usage/cost, and evaluating agent or model output quality in production.
• Experience building and consuming REST APIs, webhooks, and system‑to‑system integrations connecting AI platforms to enterprise systems.
• Microsoft Power Automate and Power Platform: building and maintaining automated workflows.
• Understanding of AI governance and security practices — guardrails, access control, and auditability for production AI systems.
• Exposure to MLOps/LLMOps concepts (model and prompt versioning, safe rollout practices) is an asset.

Working Conditions:

Typical office environment.

Please note:

Mastronardi Produce has accommodation processes and policies in place and provides accommodation for employees with disabilities. If you require a specific accommodation because of a disability or documented medical need, please contact the Human Resource office so that arrangements can be made for the appropriate accommodation to be put into place.

Equal Opportunity Employer

This employer is required to notify all applicants of their rights pursuant to federal employment laws.For further information, please review the Know Your Rights notice from the Department of Labor.