Senior DevOps/SRE Engineer (Cloud)

Overview

Provide support, automation, and infrastructure expertise for Johnson Controls IoT SaaS offerings, with a focus on cloud environments, particularly Microsoft Azure.

What you'll do

• Deliver automation and configuration management for platform infrastructure and provide stable environments for reliable, high-quality delivery.
• Automate build and deployment activities for code and data to enable continuous integration and continuous deployment.
• Create deployment strategies that enable consistent application delivery across environments and maintain configuration-management tools, code, and modules.
• Implement monitoring and logging solutions to identify system bottlenecks and production issues.
• Apply Generative AI and AI-enabled capabilities to improve DevOps, SRE, platform-engineering, troubleshooting, knowledge discovery, and operational automation workflows.
• Collaborate with software engineering, security, and operations teams to improve reliability, delivery speed, standardization, and operational efficiency.

What you'll need

• Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent practical experience.
• 3-5 years of overall industry experience working on enterprise IT or cloud-platform projects.
• Ability to build and improve CI/CD pipelines in collaboration with global engineering teams.
• 3+ years of hands-on Kubernetes experience, including deployment, scaling, troubleshooting, configuration, and production operations.
• 3+ years of hands-on experience with at least one major cloud platform: Microsoft Azure, AWS, or Google Cloud.
• 2+ years of experience with orchestration, workflow, or CI/CD tools such as Argo CD, Tekton, Jenkins, Azure DevOps, GitHub Actions, or equivalent tools.
• 3+ years of experience in infrastructure and operational automation using Terraform, Ansible, Python, PowerShell, Bash, or equivalent technologies.
• 2+ years of experience with monitoring and observability tools such as Azure Monitor, Application Insights, Grafana, Prometheus, Datadog, Dynatrace, or the ELK stack.
• 2+ years of hands-on experience with Generative AI (GenAI) and AI-enabled engineering solutions, including copilots, AI agents, prompt engineering, retrieval-augmented generation (RAG), large language model (LLM) integrations, or AI-driven automation for DevOps, SRE, platform-engineering, or software-delivery workflows.
• Working knowledge of responsible AI practices, data protection, access control, model-output validation, and secure integration of enterprise data with AI-enabled solutions.
• Excellent written and verbal communication skills, including the ability to explain complex technical concepts clearly to technical and non-technical stakeholders.
• Experience implementing, maintaining, and improving continuous integration, testing, delivery, and deployment environments.
• Working knowledge of Linux, Git, container registries, secrets management, infrastructure security, and production-support practices.

Nice to have

• Microsoft Azure experience is preferred; equivalent AWS or Google Cloud experience is also applicable.
• Strong hands-on experience with Microsoft Azure services and Azure-native operational tooling.
• Experience implementing GenAI or AI use cases using Microsoft Azure OpenAI Service, Microsoft Copilot, GitHub Copilot, or equivalent technologies.
• Experience designing or integrating RAG solutions, AI agents, prompt workflows, LLM APIs, vector search, or enterprise knowledge assistants.
• Understanding of networking concepts such as DNS, DHCP, subnets, load balancing, reverse proxies, NGINX, and firewalls.
• Experience with Terraform, Jenkins, Argo CD, Tekton, SonarQube, JFrog Artifactory, Consul, Vault, and package-management solutions.

Details

• Location: Pune, Maharashtra, India.