Johnson Controls
Johnson Controls
Johnson Controls izstrādā viedās ēku tehnoloģijas, programmatūru un pakalpojumus iekštelpu vides un ēku kritisko sistēmu pārvaldībai. Tās risinājumu klāstā ietilpst HVAC iekārtas, ēku automatizācijas un vadības sistēmas, rūpnieciskā aukstumtehnika, ugunsgrēka atklāšanas sistēmas, drošības sistēmas un digitāli enerģijas pārvaldības rīki. Izmantojot tādus risinājumus kā OpenBlue, Johnson Controls palīdz organizācijām uzraudzīt ēku veiktspēju, uzlabot darbības efektivitāti un virzīties uz ilgtspējas mērķu sasniegšanu. Uzņēmums apkalpo klientus dažādās nozarēs, tostarp būvniecībā, veselības aprūpē un loģistikā, un tā darbību atbalsta globāla darbinieku komanda.

Senior Azure DevOps Engineer (Hybrid) — Johnson Controls, York, PA

Operate Azure platforms, delivery pipelines, hybrid infrastructure, and AI services supporting Johnson Controls’ production and business systems. Coordinate secure deployments and production reliability across cloud, on-premises, and plant environments.

Apraksts

  • Operate platforms that support revenue, production, and AI workloads
  • Build and run CI/CD pipelines, environments, infrastructure as code, observability, security controls, and deployment processes
  • Administer Azure DevOps organizations and projects, YAML pipelines, repositories, branch rules, artifact feeds, service connections, environments, and self-hosted agents
  • Create controlled release processes for microservices, integrations, APIs, and commercial platforms such as CPQ, PLM, ERP, and MES
  • Define approval steps, change records, and audit evidence
  • Schedule and carry out deployments around maintenance windows, shifts, quarter-end demand, and factory operations
  • Manage infrastructure as code and Azure services, including Functions, Azure SQL, storage, Service Bus, Event Hubs, API Management, and data platforms
  • Manage network and identity services, including VNets, private endpoints, hub-and-spoke networks, ExpressRoute, site-to-site VPN, Entra ID, managed identities, Key Vault, and RBAC
  • Operate hybrid and edge infrastructure with Azure Arc, IoT Edge, and IoT Hub
  • Set environment strategy and manage lifecycle across development, test, UAT, and production
  • Refresh and provision environments and mask test data
  • Deploy and operate Azure Machine Learning or Azure AI Foundry, including workspaces, compute, GPU capacity, model registries, and managed inference endpoints
  • Manage Azure OpenAI and other model provider access, quotas, throughput, private networking, content filters, keys, and identity
  • Extend CI/CD to AI workloads with version control, automated evaluation gates, and rollback processes
  • Monitor AI workloads in production, tracking latency, errors, abstention rates, token use, drift, and feature costs
  • Deploy inference workloads to cloud, on-premises, or plant-edge environments
  • Manage and forecast AI costs
  • Create business-impact monitoring and alerts; own SLOs, dashboards, and production incident response
  • Lead incident management and blameless post-incident reviews
  • Maintain security controls through secrets management, vulnerability and dependency scans, container image hygiene, SBOM generation, and patch coordination
  • Work with IT, OT, and information security teams on network segmentation, access control, and compliance
  • Improve delivery with self-service environments, reusable pipeline templates, and documentation
  • Coach engineers in deployment, observability, and operational ownership

Prasības

  • At least five years of experience in DevOps, platform, SRE, or cloud infrastructure engineering
  • Practical Azure experience spanning compute, networking, identity, data services, and monitoring
  • Strong Azure DevOps skills, including YAML pipelines, self-hosted agents, environments and approvals, artifact management, and repository governance
  • Comparable experience with GitHub Actions or GitLab CI is acceptable if you can demonstrate readiness to learn Azure DevOps
  • Production experience with Docker containers and Kubernetes orchestration
  • Automation and scripting skills in Python and PowerShell or Bash
  • Experience deploying to hybrid environments, including firewalled systems, private connections, and on-premises servers
  • Track record of owning production systems, including on-call duties, incident response, and measurable reliability improvements
  • Preferred: MLOps experience with Azure Machine Learning, model registries, inference endpoints, GPU capacity management, or LLMOps
  • Preferred: Experience supporting ERP, PLM, CPQ, MES, or integration middleware
  • Preferred: Manufacturing or industrial experience, including OT network segmentation and plant cybersecurity practices
  • Preferred: Data platform operations involving Data Factory or Fabric, warehouse or lakehouse infrastructure, and orchestration
  • Preferred: Experience with FinOps practices
  • Preferred: Azure certifications such as AZ-400, AZ-104/305, or AI-102, and Kubernetes certification such as CKA
  • Preferred: Experience as an early platform hire setting technical standards
  • Preferred: Production infrastructure-as-code experience with Terraform or Bicep, across multiple environments and with responsible state management

Priekšrocības

  • Bonus plan tied to individual, group, and company performance
  • Benefits package
  • Relocation assistance is available

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