Cloud Engineer - Azure DevOps at Miracle Hub · Mumbai · 2 - 5 years · ₹12L - ₹18L / yr · Profitable · Posted 28 Jun 2022

Job Title: Cloud Engineer - Azure DevOps
Job Location: Mumbai (Andheri East)
About the company:
MIRACLE HUB CLIENT, is a predictive analytics and artificial intelligence company headquartered in Boston, US with offices across the globe. We build prediction models and algorithms to solve high priority business problems. Working across multiple industries, we have designed and developed breakthrough analytic products and decision-making tools by leveraging predictive analytics, AI, machine learning, and deep domain expertise
Skill-sets Required:
- Azure Architecture
- DevOps Expert
- Infrastructure as a code
- Automate CICD pipelines
- Security and Risk Compliance
- Validate Tech Design
Job Role:
- Create a well-informed cloud strategy and manage the adaption process and Azure based architecture
- Develop and organize automated cloud systems
- Work with other teams in continuous integration and continuous deployment pipeline in delivering solutions
- Work closely with IT security to monitor the company's cloud privacy
Desired Candidate Profile:
- Bachelor’s degree in computer science, computer engineering, or relevant field.
- A minimum of 3 years’ experience in a similar role.
- Strong knowledge of database structure systems and data mining.
- Excellent organizational and analytical abilities.
- Outstanding problem solver.
- IMMEDIATE JOINING (A notice period of 1 month is also acceptable)
- Excellent English communication and presentation skills, both verbal and written
- Charismatic, competitive and enthusiastic personality with negotiation skills
Compensation: 12-15 LPA with minimum 5 years of experience. ( OR AS PER LAST DRAWN )

About Miracle Hub
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Position Summary
We are seeking a hands-on Mid-Level Azure Cloud Engineer to manage, maintain, and optimize
our Microsoft Azure environment. The ideal candidate has strong experience across Azure
infrastructure, networking, security, identity, automation, and cloud operations, and can
independently support day-to-day cloud administration and deployments.
Responsibilities
Manage and maintain Azure infrastructure, including virtual networks, virtual machines,
storage, Azure SQL, App Services, Key Vault, and Azure Functions.
Administer Microsoft Entra ID (Azure AD), RBAC, Conditional Access, and
identity/security policies.
Monitor cloud health, performance, costs, and security using Azure Monitor, Log
Analytics, and Microsoft Defender.
Implement and maintain Infrastructure as Code (Terraform, Bicep, or ARM templates).
Support CI/CD pipelines using Azure DevOps and Git.
Configure backups, disaster recovery, high availability, and business continuity solutions.
Troubleshoot Azure networking, application, and infrastructure issues.
Work closely with development, security, and infrastructure teams to ensure reliable
cloud operations.
Qualifications
4–7 years of Azure cloud engineering experience.
Strong hands-on experience with Azure networking, compute, storage, App Services,
Azure SQL, Key Vault, and Azure Monitor.
Experience with Microsoft Entra ID (Azure AD), RBAC, MFA, Conditional Access, and
identity management.
Experience with Azure DevOps, Git, CI/CD, PowerShell, and Infrastructure as Code
(Terraform, Bicep, or ARM).
Knowledge of cloud security, governance, backup, disaster recovery, and cost
optimization.
Strong troubleshooting, documentation, and communication skills.
Experience supporting production cloud environments in an enterprise setting.
Preferred Skills
Experience with Kubernetes (AKS), Docker, Azure API Management, Azure Front Door,
and Microsoft Defender for Cloud.
Azure Administrator (AZ-104) or Azure Solutions Architect (AZ-305) certification
preferred.
Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent experience.

Position Summary
We are seeking a hands-on Mid-Level Azure Cloud Engineer to manage, maintain, and optimize our Microsoft Azure environment. The ideal candidate has strong experience across Azure infrastructure, networking, security, identity, automation, and cloud operations, and can
independently support day-to-day cloud administration an deployments.
Responsibilities
Manage and maintain Azure infrastructure, including virtual networks, virtual machines,
storage, Azure SQL, App Services, Key Vault, and Azure Functions.
Administer Microsoft Entra ID (Azure AD), RBAC, Conditional Access, and
identity/security policies.
Monitor cloud health, performance, costs, and security using Azure Monitor, Log
Analytics, and Microsoft Defender.
Implement and maintain Infrastructure as Code (Terraform, Bicep, or ARM templates).
Support CI/CD pipelines using Azure DevOps and Git.
Configure backups, disaster recovery, high availability, and business continuity solutions.
Troubleshoot Azure networking, application, and infrastructure issues.
Work closely with development, security, and infrastructure teams to ensure reliable cloud operations.
Qualifications
4–7 years of Azure cloud engineering experience.
Strong hands-on experience with Azure networking, compute, storage, App Services, Azure SQL, Key Vault, and Azure Monitor.
Experience with Microsoft Entra ID (Azure AD), RBAC, MFA, Conditional Access, and identity management.
Experience with Azure DevOps, Git, CI/CD, PowerShell, and Infrastructure as Code (Terraform, Bicep, or ARM).
Knowledge of cloud security, governance, backup, disaster recovery, and cost optimization.
Strong troubleshooting, documentation, and communication skills.
Experience supporting production cloud environments in an enterprise setting.
Preferred Skills
Experience with Kubernetes (AKS), Docker, Azure API Management, Azure Front Door, and Microsoft Defender for Cloud.
Azure Administrator (AZ-104) or Azure Solutions Architect (AZ-305) certification preferred.
Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or
equivalent experience.
Applications on this job are not being reviewed actively. You may apply but please follow up with the company via other channels too.
Tasks & Responsibilities: (Major task and role person will have to perform – list all the relevant points)
Together with the Business Cloud Services team, you will design, deploy, and operate a cloud‑native Kubernetes PaaS platform on Azure, ensuring high availability, security, and operational excellence.
Your main duties include:
· Drive cloud‑native automation and self‑service capabilities, ensuring platform security, availability, and disaster recovery readiness
· Design, operate, and continuously improve Kubernetes clusters and PaaS environments on Azure / AKS
· Collaborate closely with development teams on deployment strategies, operational requirements, and platform integration
· Review and maintain infrastructure‑as‑code configurations, CI/CD pipelines, and cloud‑native deployments
· Build and maintain CI/CD pipelines using Azure DevOps
· Implement and operate infrastructure‑as‑code solutions using Terraform, Helm, and Ansible
· Manage containerized workloads and orchestration across cloud‑native environments
· Set up, operate, and enhance monitoring, logging, and alerting stacks using tools such as Prometheus and Grafana
· Coordinate with support teams on platform incidents, escalations, and post‑incident analysis
· Contribute to incident response, continuous improvement, and operational stability
· Support the development and refinement of DevOps practices, runbooks, and operational standards
· Actively contributes to improving developer experience and platform reliability
Education & Trainings + Certifications: (Basic & Professional)
· Bachelor’s degree (Preferably engineering graduate)
· Azure Solutions Architect Expert Certification is a plus.
· (optional) ITIL Foundation
Technical know-how: (Mention the technology on which person must be experienced)
Mandatory
o Bachelor’s degree in computer science, Information Systems, or a related field
o 5+ years of relevant professional experience in DevOps, Cloud Engineering, or Platform Engineering roles
o Strong Linux system administration skills for operating production‑grade cloud‑native platforms
o Proven experience with Microsoft Azure, including AKS and Azure DevOps tooling
o Strong expertise in Kubernetes, including cluster operations, RBAC, networking, and storage
o Hands‑on experience with container technologies such as Docker and container registries
o Proficiency with Terraform, Helm, Ansible, and PowerShell
o Experience building and operating CI/CD pipelines using Azure DevOps or equivalent tools
o Cloud‑native monitoring and observability experience using Prometheus, Grafana, and alerting pipelines
o Solid understanding of security and compliance requirements such as PCI DSS and SOC2
o Scripting skills for automation and tooling (Bash, Python, PowerShell)
o Practical experience using Git for version control
o Excellent communication skills in English (Spanish is a plus)
o Automation‑first mindset and strong collaboration skills within Agile teams
Good to know
Principles of Agile Software Development.
· GitHub Actions, GitLab CI, Jenkins, Azure DevOps
· Containers: Docker, Kubernetes (EKS / AKS / GKE)
· Configuration Management: Ansible
TECHJAYS
THE AI REIMAGINATION COMPANY
Position DevOps Lead
Experience 10+ Years
Location Coimbatore / Hybrid
Joining Immediate / ASAP
Primary SkillsDevOps, AWS or Azure, CI/CD, Kubernetes, Docker, Terraform, Linux, Git, Cloud Infrastructure, Infrastructure Automation, Monitoring & Observability
Preferred SkillsAI/ML Infrastructure Exposure, GenAI Applications, GitOps, Argo CD, Prometheus, Grafana, Python, Bash, PowerShell, Cloud Security, FinOps
About Techjays
At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing secure, scalable, production-grade AI systems that solve complex business challenges and deliver measurable business outcomes.
Our team brings together experienced engineers and technology leaders from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build advanced AI-powered applications, enterprise platforms, and intelligent automation solutions.
We're looking for a DevOps Lead who can take ownership of cloud infrastructure, deployment automation, CI/CD pipelines, platform reliability, and engineering operations.
The ideal candidate will have deep hands-on expertise in either AWS or Azure, along with strong experience in Kubernetes, containerization, Infrastructure as Code, and production cloud environments.
You will lead the design and implementation of reliable infrastructure platforms, establish DevOps best practices, and work closely with software engineering and AI teams to support the deployment and operation of modern applications.
This role requires a strong hands-on cloud and DevOps specialist who can architect, implement, troubleshoot, and optimize production infrastructure. Prior exposure to AI/ML or AI-enabled applications is required, but specialized MLOps expertise is not mandatory.
Key Responsibilities
1. Cloud Infrastructure & Architecture
- Lead the design, implementation, and management of scalable, secure, and highly available cloud infrastructure.
- Own cloud infrastructure architecture and operations across AWS or Azure.
- Design and manage cloud environments covering compute, networking, storage, databases, and container platforms.
- Establish infrastructure standards, architecture patterns, and operational best practices.
- Manage cloud resource provisioning, configuration, scaling, and environment management.
- Ensure infrastructure meets requirements for availability, performance, security, and reliability.
- Drive infrastructure improvements through automation and continuous optimization.
2. DevOps & CI/CD Engineering
- Design, implement, and maintain CI/CD pipelines for application development and deployment.
- Manage multi-stage deployment workflows across development, testing, staging, and production environments.
- Implement automated build, testing, deployment, and release processes.
- Establish reusable pipeline templates, deployment standards, and approval workflows.
- Manage deployment strategies, including rolling, blue/green, and canary deployments.
- Implement rollback mechanisms and ensure reliable production releases.
- Integrate CI/CD workflows with source control, artifact repositories, and container registries.
- Continuously improve deployment efficiency, release reliability, and engineering productivity.
3. Containerization & Kubernetes Management
- Architect and manage containerized application environments using Docker and Kubernetes.
- Manage production Kubernetes clusters using Amazon EKS or Azure AKS.
- Implement Kubernetes configurations covering deployments, services, networking, secrets, storage, and resource management.
- Work with Helm charts for application packaging and deployment.
- Optimize container resource utilization, application scaling, and cluster performance.
- Troubleshoot complex container and Kubernetes-related production issues.
- Establish best practices for container security and workload reliability.
4. Infrastructure as Code & Automation
- Implement Infrastructure as Code using Terraform and cloud-native provisioning tools.
- Automate infrastructure provisioning, configuration management, and environment setup.
- Develop reusable infrastructure modules and deployment automation workflows.
- Use Python, Bash, or PowerShell to automate operational tasks and improve efficiency.
- Reduce manual intervention through standardization and automation.
- Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.
5. Monitoring, Reliability & Production Operations
- Establish centralized monitoring, logging, alerting, and observability across cloud environments.
- Implement monitoring solutions using CloudWatch, Azure Monitor, Prometheus, Grafana, or equivalent platforms.
- Monitor application availability, infrastructure health, resource utilization, and system performance.
- Lead troubleshooting and resolution of complex production incidents.
- Conduct root cause analysis and implement permanent corrective actions.
- Establish operational practices for backup, disaster recovery, availability, and business continuity.
- Improve system reliability through proactive monitoring and performance optimization.
6. Cloud Security & Governance
- Implement cloud security best practices across infrastructure and application environments.
- Manage IAM, RBAC, access controls, service identities, and secrets management.
- Secure cloud networking, virtual networks, firewalls, and infrastructure access.
- Implement container security and infrastructure hardening practices.
- Ensure cloud environments follow organizational security and compliance requirements.
- Identify infrastructure vulnerabilities and coordinate remediation activities.
- Establish secure deployment and configuration management practices.
7. AI Infrastructure & Engineering Collaboration
- Work closely with AI/ML and software engineering teams to provide infrastructure for AI-powered applications.
- Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
- Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
- Support the infrastructure requirements of AI applications across development, testing, and production environments.
- Collaborate with engineering teams to improve deployment reliability, scalability, and operational performance of AI-powered systems.
- Evaluate infrastructure technologies and tools that support evolving AI application requirements.
8. Technical Leadership & Team Development
- Provide technical leadership to DevOps engineers and guide implementation across projects.
- Establish engineering standards, infrastructure best practices, and operational procedures.
- Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
- Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
- Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
- Drive continuous improvement across DevOps processes, tools, and engineering practices.
Required Technical Skills & Experience
1. Cloud Platforms
- 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
- Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
- Practical experience designing, deploying, and operating production-grade cloud infrastructure.
AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.
Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.
Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.
2. DevOps & CI/CD
- Strong experience designing and maintaining CI/CD pipelines.
- Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
- Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
- Experience implementing deployment automation and rollback strategies.
- Strong understanding of Git workflows and version control practices.
3. Containers & Kubernetes
- Strong hands-on experience with Docker and Kubernetes.
- Practical experience managing EKS or AKS environments.
- Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
- Experience with Helm and container orchestration.
- Ability to troubleshoot production container and Kubernetes environments.
4. Infrastructure as Code & Scripting
- Strong experience with Terraform and Infrastructure as Code practices.
- Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
- Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
- Strong understanding of Linux administration and system troubleshooting.
5. Monitoring & Reliability Engineering
- Experience implementing infrastructure and application monitoring.
- Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
- Understanding of incident management, root cause analysis, performance optimization, and system availability.
- Experience establishing alerting, operational dashboards, and reliability practices.
6. AI/ML Infrastructure Exposure
- Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
- Understanding of infrastructure requirements for deploying and operating AI-powered applications.
- Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.
Note: This role does not require specialized MLOps expertise or model development experience. Strong cloud and DevOps engineering fundamentals remain the primary requirement.
Preferred Skills
- Experience implementing GitOps workflows using Argo CD or similar tools.
- Experience with blue/green deployments, canary releases, and automated rollback mechanisms.
- Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
- Experience with cloud cost optimization and FinOps practices.
- Familiarity with AI/ML infrastructure and production GenAI applications.
- Experience with Python-based automation and infrastructure tooling.
- Relevant AWS, Azure, Kubernetes, or Terraform certifications.
What We're Looking For Beyond Skills
- Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
- Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
- Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
- System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
- Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
- Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
- Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
- AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
- Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.
Typical Technology Environment
AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products
What We Offer
- Competitive compensation aligned with experience and expertise.
- Coimbatore office-based work environment with hybrid flexibility.
- Opportunity to lead cloud infrastructure and DevOps engineering for global clients.
- Exposure to modern AWS/Azure, Kubernetes, automation, and AI engineering practices.
- Paid holidays and flexible time off.
- Medical insurance covering self and family, up to ₹4 lakh per person.
- Opportunities to influence infrastructure architecture and engineering practices.
- A culture that values clarity, integrity, ownership, and continuous growth.
Join Techjays
If you're passionate about building reliable cloud platforms, automating complex infrastructure, and leading DevOps engineering for modern AI-powered applications, we'd love to hear from you.

About the company:
We empower US healthcare payers with a truly next-generation, cloud-native, holistic, and customizable platform designed to prevent and adapt to the ever-evolving inaccuracies in healthcare claims and payments. By reducing complexity and administrative costs, we offer a unified, healthcare-dedicated platform backed by top VCs like BeeNext, 3One4 Capital, and Saison Capital.
Position Overview:
We are looking for an experienced DevOps Engineer to join our team in Bengaluru. In this role, you will be responsible for building, optimizing, and maintaining scalable, secure, and highly available multi-cloud infrastructure that supports our engineering teams. The ideal candidate brings strong hands-on experience with Kubernetes, Infrastructure as Code (Terraform), and robust monitoring/observability stacks to enable seamless, reliable, and automated deployments.
Key Responsibilities:
- Container Orchestration: Deploy, scale, and manage containerized workloads on Kubernetes (EKS, AKS, and GKE).
- Infrastructure as Code (IaC): Build and maintain modular, reusable, and version-controlled infrastructure using Terraform across AWS, Azure, and GCP.
- Monitoring & Observability: Set up, manage, and optimize monitoring, logging, and alerting stacks (e.g., Prometheus, Grafana, ELK/EFK, Loki, Datadog).
- CI/CD Pipeline Management: Own, improve, and automate CI/CD pipelines to enable fast, reliable, and frictionless software releases.
- System Reliability & SRE Practices: Implement best practices for system reliability, including defining SLIs/SLOs, managing incident response, and participating in on-call support.
- Troubleshooting & Support: Diagnose and resolve complex production issues across infrastructure, networking, and application layers.
- Security & Compliance: Implement infrastructure security best practices, including IAM policies, secrets management, and network security.
- Automation: Eliminate repetitive operational tasks by writing clean, efficient scripts in Python, Bash, or Go.
- Operations & Planning: Participate in capacity planning, cost optimization, disaster recovery, and infrastructure scaling initiatives while maintaining clear documentation and runbooks.
Requirements :
- Solid working experience with cloud providers, specifically AWS, Azure, or GCP.
- Strong understanding of containerization (Docker) and container orchestration concepts.
- Familiarity with Linux system administration and networking fundamentals.
- Experience with version control systems (Git) and GitOps workflows (ArgoCD/Flux is a plus).
- Strong problem-solving skills and the ability to thrive in a fast-paced, collaborative environment.
Qualifications :
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related technical field (or equivalent practical experience)
Key Skills:
- The ideal candidate must possess deep expertise in container orchestration, specifically hands-on experience managing Kubernetes ecosystems—including Helm charts, cluster networking, and RBAC policies—alongside a foundational mastery of Docker containerization.
- Proficiency in managing cloud architecture as software is essential, with a heavy emphasis on Terraform execution, including advanced module creation, state management, and multi-environment workspaces.
- A strong capability to implement full-stack visibility is required, utilizing tools like Prometheus, the Grafana LGMT stack, ELK/EFK, or Loki to build highly optimized monitoring, alerting, and logging systems.
- Candidates should have a proven track record of constructing and scaling automated deployment pipelines using industry-standard platforms such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps to minimize release friction. .
- Strong core programming fundamentals are required to automate repetitive infrastructure tasks, with practical proficiency in Python, Bash, or Go.
- Familiarity with cutting-edge cloud-native technologies is highly desirable, including enterprise service meshes (Istio, Linkerd), comprehensive cloud security frameworks (HashiCorp Vault, OPA, Trivy), and a data-driven approach to cloud cost management and FinOps practices.
Work Location: Jayanagar - Bangalore.
Work Mode: Work from Office, hybrid- 3 days WFO
Note: We are looking for immediate joiners & Bangalore Candidates only
Benefits:
- Best-in-class compensation
- Health insurance for Family
- Personal Accident Insurance
- Friendly and Flexible Leave Policy
- Certification and Course Reimbursement
- Medical Coding CEUs and Membership Renewals
- Health checkup
- And many more!
Summary -
- We are looking for a Cloud Infrastructure Engineer to build and operate the Azure foundation for our AI workloads and serve as the working bridge between the Cloud Infrastructure and Data teams. You will own Terraform-driven Azure infrastructure, DevOps pipelines, and hands-on platform components, including Azure AI Foundry, Model Context Protocol (MCP) servers, and Databricks.
Responsibilities -
- Build and maintain Azure infrastructure as code with Terraform, including reusable modules and multi-environment patterns.
- Provision and operate Azure AI Foundry hubs and projects, including model deployments, data connections, and identity and network configuration.
- Design and secure MCP servers that expose internal tools and data to AI agents.
- Partner with the Data team to deploy and configure Databricks workspaces, including VNet injection, private endpoints, Entra ID integration, and Unity Catalog.
- Own CI/CD pipelines in Azure DevOps or GitHub Actions for infrastructure and AI platform deployments.
- Enforce guardrails for AI workloads, including Key Vault secrets management, managed identities, and network isolation.
- Monitor platform health, reliability, and cost with Azure Monitor and Log Analytics.
- Triage cross-team platform requests, document reference patterns, and remove blockers between Cloud and Data teams.\
Requirements -
- 4 to 8 years of experience in cloud infrastructure or platform engineering.
- Strong hands-on Azure experience, including networking, Entra ID, RBAC, and managed identities.
- Advanced Terraform skills, including module design and state management.
- Working knowledge of DevOps practices, CI/CD, and Git-based workflows.
- Working knowledge of Azure AI Foundry or Azure OpenAI, including access control and network integration.
- Practical understanding of MCP and the security considerations for connecting AI agents to enterprise systems.
- Hands-on Databricks platform experience, including workspace deployment, Unity Catalog, and cluster configuration.
- Scripting skills in Python, PowerShell, or Bash.
- Experience working within SOC 2 Type II or similar control frameworks.
Preferred Qualifications -
- Experience with RAG architectures or Azure AI Search.
- Experience with GPU capacity and quota planning in Azure.

Senior Azure DevOps Engineer
Experience: 8+ years(including 4+ years running production workloads on Microsoft Azure)
Job Type : Contract,Remote(C2C,only inhouse profiles; independent contractors)
Work Hours: 2:00 pm to 11:00 pm IST (8-hour shift with a 1-hour break)
Duration: 6 months (Extendable)
The Role
Own the path from commit to production, and the running of live systems afterward, for enterprise client programmes on Azure. Releases are controlled by the pipeline: build once, promote the same artefact through every environment, verify on the running system, and roll back automatically on failure. About 70% hands-on, 30% client engagement, mentoring and reporting.
What You'll Do
- Build and run Azure DevOps CI/CD with digest-based promotion, health-gated slot swaps and automatic rollback
- Operate live production systems to agreed service levels, including incidents, DR testing, patching and cost control
- Manage all infrastructure through Terraform with drift detection, Key Vault, managed identities and private networking
- Integrate automated test and security gates into pipelines
- Work directly with the client's engineers and directors in design reviews, change approvals and incident calls
- Use AI tools for pipelines, scripts and incident triage, with every output reviewed and tested
- Direct and review junior DevOps engineers
Must-Haves
- Azure production experience (App Service, Functions, Container Apps or AKS, VNets, Key Vault)
- Azure DevOps multi-stage YAML, environments, approvals and service connections
- Production Terraform
- Docker, PowerShell, Bash, Python or Node.js, Azure CLI
- CI/CD test gates and static or security scanning
- On-call, incident, problem and change management, with App Insights, Azure Monitor and KQL
- Client-facing experience and clear English
- Experience leading juniors and working independently
- BE/BTech in CS, IT or equivalent
Nice-to-Have
AZ-400, AZ-104, AZ-305, Terraform Associate, ITIL 4; Azure Policy; AKS, GitHub Actions or Bicep; AI/LLM workloads in production
- Strong hands-on experience in Microsoft Azure Cloud.
- Good understanding of Azure services such as Compute, Storage, Event Hub, Event Subscription, Storage Queue, and PaaS services.
- Basic understanding of Azure AI Foundry and AI-related Azure service setup.
- Good Azure networking basics: VNet, subnet, routing, and basic troubleshooting.
- Strong knowledge of Terraform, especially:
- Terraform state
- plan / apply
- troubleshooting failures
- migration risks
- Terraform Enterprise concepts
- Strong Python coding capability, not just basic scripting.
- Experience using Python for API integration, automation, JSON/YAML handling, and internal tooling.
- Good understanding of CI/CD pipelines.
- Ability to troubleshoot pipeline failures.
- Comfortable with YAML and JSON.
- Ability to troubleshoot Azure infrastructure/platform issues.
- Ability to collect logs/evidence and coordinate with network/app/Microsoft support teams.
- Basic awareness of agentic AI / LLM concepts.
- Awareness of security and cost best practices.
Good to Have Skills
- Hands-on experience with Harness.
- Hands-on experience with Terraform Enterprise.
- Exposure to LangGraph / LangChain.
- Exposure to agentic AI workflows or skill creation.
- Exposure to Claude or enterprise LLM integrations.
- Knowledge of Azure ML Workspace, model registry, and managed endpoints.
- MLOps / LLMOps knowledge.
- FinOps / Azure cost optimization experience.
- Azure certifications: AZ-104, AZ-305, AZ-400, AZ-500.
Screening Priority:
Azure Cloud + Terraform + Python Coding + CI/CD Troubleshooting + YAML/JSON + Basic Agentic AI Awareness
Applications on this job are not being reviewed actively. You may apply but please follow up with the company via other channels too.
Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent experience).
3+ years of hands-on experience with Microsoft Azure, including IaaS, PaaS, networking, identity (Entra ID), and governance services.
2+ years of experience with DevOps tooling and practices, including CI/CD pipelines (Azure DevOps or GitHub Actions), Infrastructure as Code (Terraform, Bicep, or ARM), and version control (Git).
2+ years' experience in infrastructure design, platform engineering, or architecture.
Strong proficiency with automation and scripting — PowerShell, Azure CLI, Python, or Bash.
Solid understanding of containerisation (Docker) and familiarity with orchestration platforms (Azure Kubernetes Service).
Deep understanding of cloud architecture, deployment patterns, and management best practices, including the Azure Well-Architected Framework.
Experience defining standards, governance frameworks, and reference architectures for cloud platform consumption.
Strong knowledge of networking concepts, storage configurations, virtualisation technologies, and disaster recovery/backup design for hybrid environments.
Experience with Azure DevOps (Repos, Pipelines, Boards, Artifacts) or equivalent platforms.
Familiarity with identity and access management (IAM), including Entra ID, RBAC, PIM.
Strong understanding of security, compliance requirements, and IT governance frameworks (ITIL, COBIT, or similar).
Preferred
Applications on this job are not being reviewed actively. You may apply but please follow up with the company via other channels too.
Job Summary:
We are looking for an experienced Cloud / DevOps Engineer with strong hands-on experience in AWS, Kubernetes, OpenShift, and Linux. The candidate will be responsible for managing cloud infrastructure, containerized applications, deployments, and production environments.
Roles & Responsibilities:
- Design, deploy, and manage cloud infrastructure on AWS.
- Manage and administer Kubernetes and OpenShift environments.
- Deploy, configure, and troubleshoot containerized applications.
- Perform Linux administration, troubleshooting, and system monitoring.
- Monitor application and infrastructure performance and resolve production issues.
- Automate deployment and operational activities wherever possible.
- Work with development and operations teams to support application deployments.
- Ensure system availability, reliability, and security.
- Troubleshoot issues related to Kubernetes clusters, containers, networking, and Linux systems.
- Follow DevOps best practices for CI/CD, infrastructure management, and automation.
Required Skills:
- 7–10 years of relevant experience in Cloud/DevOps.
- Strong hands-on experience with AWS.
- Good knowledge of Kubernetes and OpenShift.
- Strong Linux administration and troubleshooting skills.
- Experience in containerization and deployment of applications.
- Good understanding of cloud infrastructure and production support.










