DevOps Architect(Azure Ai)

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

Experience: 4+ Years 

Job Title: DevOps Engineer / Cloud Engineer 

Job Summary 

We are looking for an experienced DevOps & Cloud Engineer with 4+ years of experience in cloud infrastructure management, Kubernetes administration, CI/CD pipeline automation, and containerization. The ideal candidate should have hands-on experience with Azure cloud services, Azure Kubernetes Service (AKS), Azure DevOps, Jenkins, Docker, Terraform, and infrastructure automation. 

The candidate will be responsible for managing cloud environments, automating application deployments, maintaining Kubernetes clusters, monitoring system performance, and ensuring the reliability, scalability, security, and availability of applications across development, testing, and production environments. 

Key Responsibilities 

• Design, deploy, and manage cloud infrastructure using Microsoft Azure services, including Virtual Machines, Virtual Networks, Storage Accounts, Load Balancers, Key Vaults, and Resource Groups. 
• Manage and administer Azure Kubernetes Service (AKS), Azure Arc-enabled Kubernetes, and Kubernetes clusters. 
• Develop, configure, and maintain CI/CD pipelines using Azure DevOps and Jenkins for automated application builds, testing, and deployments. 
• Containerize applications using Docker and deploy microservices-based applications on Kubernetes. 
• Manage Kubernetes resources, including Pods, Deployments, StatefulSets, Services, Ingress, ConfigMaps, Secrets, and Namespaces. 
• Automate infrastructure provisioning and configuration management using Terraform, Ansible, and Infrastructure as Code (IaC) practices. 
• Implement Kubernetes networking, load balancing, Role-Based Access Control (RBAC), autoscaling, and resource optimization. 
• Monitor infrastructure and application performance using Prometheus and Grafana. 
• Troubleshoot application, deployment, networking, container, and infrastructure-related issues and perform root cause analysis. 
• Implement disaster recovery procedures, backup validation, failover testing, patch management, and environment upgrades. 
• Manage source code repositories, branching strategies, pull requests, code merges, and version control using Git, GitHub, and Azure Repos. 
• Maintain cloud infrastructure security, compliance, governance, high availability, and operational reliability. 
• Collaborate with development, infrastructure, and security teams to implement DevOps best practices and improve deployment efficiency. 

Mandatory Technical Skills 

1. Cloud Platforms: Microsoft Azure, Azure Virtual Machines, Virtual Networks, Storage Accounts, Load Balancers, Key Vaults. 
2. Containerization & Orchestration: Docker, Kubernetes, Azure Kubernetes Service (AKS). 
3. CI/CD & Automation: Azure DevOps, Jenkins, CI/CD pipeline development and maintenance. 
4. Infrastructure as Code: Terraform; exposure to Ansible and automated configuration management. 
5. Monitoring & Version Control: Prometheus, Grafana, Git, GitHub, Azure Repos. 

Preferred Skills 

• Azure Arc-enabled Kubernetes. 
• VMware Tanzu Kubernetes Grid (TKG). 
• Kubernetes Service Mesh, Ingress Controllers, and Horizontal Pod Autoscaling (HPA). 
• RHEL Linux administration and Shell Scripting. 
• Groovy scripting and SQL fundamentals. 
• Disaster recovery, incident management, and production support. 
• Experience supporting microservices architectures and application migration activities. 

Qualifications 

• Bachelor’s degree in Engineering (B.E.) or an equivalent qualification. 
• 4+ years of experience in DevOps engineering, cloud infrastructure, Kubernetes administration, and deployment automation. 
• Strong troubleshooting, analytical, and problem-solving skills. 
• Ability to work collaboratively with cross-functional teams and manage infrastructure-related incidents. 

Key Deliverables 

• Reliable, scalable, and secure cloud infrastructure. 
• Automated and efficient CI/CD pipelines. 
• Stable Kubernetes clusters and containerized application deployments. 
• Reduced infrastructure provisioning and deployment time through automation. 
• Effective monitoring, incident resolution, and disaster recovery readiness. 

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

Job Title : DevOps Engineer

Experience : 7+ Years

Working Hours : 3:30 AM – 11:30 AM ET

Duration : 12–18 Months

Engagement : Contract

Freelance : Not Applicable

BGV : Required

Role Overview :

We are looking for an experienced DevOps Engineer to design, implement, and optimize DevOps practices, CI/CD pipelines, deployment automation, and cloud-native delivery platforms. The role will focus on enabling secure, reliable, and efficient software delivery while improving infrastructure automation, release processes, platform reliability, and operational resilience.

Mandatory Skills :

DevOps, CI/CD, Azure DevOps / GitHub Actions, Kubernetes, Docker, PowerShell / Python / Bash, Automation, Monitoring & Observability, DevSecOps, IaC, Troubleshooting, and Production Support.

Key Responsibilities :

• Design, build, and maintain CI/CD pipelines for enterprise application delivery and release management.
• Develop deployment automation frameworks to improve release quality, consistency, scalability, and efficiency.
• Administer Kubernetes and containerized environments and supporting orchestration platforms.
• Improve build, test, deployment, and release workflows for development teams.
• Integrate automated testing, security scanning, validation, and compliance controls into CI/CD pipelines.
• Implement monitoring, logging, alerting, and observability solutions for platform and application environments.
• Troubleshoot deployment failures, production issues, and platform incidents; perform root cause analysis.
• Develop automation scripts and tools using PowerShell, Python, Bash, or similar technologies.
• Implement Infrastructure as Code and automation practices to reduce manual effort and operational risk.
• Collaborate with Cloud, Infrastructure, Security, and Application teams to deliver scalable and resilient solutions.
• Maintain deployment standards, release procedures, technical documentation, and operational runbooks.
• Apply DevOps, DevSecOps, and SRE best practices to improve delivery speed and platform reliability.
• Evaluate emerging DevOps technologies and recommend improvements.
• Mentor team members on DevOps methodologies, automation, and platform engineering practices.
• Act as an escalation point for critical deployment, infrastructure, and platform issues.

Required Technical Skills :

1. DevOps & CI/CD :

• 7+ years of experience in DevOps, Platform Engineering, Infrastructure Engineering, or Software Engineering.
• Strong experience designing and supporting CI/CD pipelines and release management.
• Hands-on experience with Azure DevOps, GitHub, GitHub Actions, or equivalent platforms.
• Strong understanding of Git, branching strategies, release management, and deployment methodologies.

2. Containers & Cloud :

• Strong hands-on experience with Kubernetes and Docker/containerization.
• Understanding of cloud-native application architectures and distributed systems.
• Experience supporting production-grade containerized environments.

3. Automation & IaC :

• Strong proficiency in PowerShell, Python, Bash, or similar scripting languages.
• Experience developing automation frameworks and deployment tooling.
• Knowledge of Infrastructure as Code (IaC) concepts.
• Experience with Terraform, Bicep, or similar tools is preferred.

4. Monitoring & Reliability :

• Experience with monitoring, logging, observability, and alerting.
• Strong troubleshooting and root cause analysis skills.
• Experience supporting highly available and resilient production systems.
• Knowledge of SRE practices is preferred.

5. Security & DevSecOps :

• Understanding of DevSecOps and secure software delivery practices.
• Experience integrating vulnerability scanning, security controls, and compliance checks into CI/CD pipelines.
• Knowledge of IAM, secrets management, and access control within DevOps environments.

Preferred Qualifications :

• Hands-on experience with Microsoft Azure.
• Experience with Terraform/Bicep or other IaC tools.
• Knowledge of SRE and platform engineering practices.
• Relevant Azure, Kubernetes, Cloud, or DevOps certifications.

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.

Job Summary

We are looking for an experienced DevOps Engineer with strong hands-on expertise in GitHub Actions, Harness CI/CD, Google Cloud Platform (GCP), and Microsoft Azure. The candidate will be responsible for designing, implementing, and maintaining CI/CD pipelines, automating cloud infrastructure deployments, and improving application delivery through DevOps best practices.

Key Responsibilities

• Design, develop, and maintain CI/CD pipelines using GitHub Actions and Harness.
• Implement automated build, test, deployment, and release workflows.
• Manage and support cloud infrastructure across GCP and Microsoft Azure.
• Configure GitHub Actions workflows, reusable workflows, secrets, runners, and deployment environments.
• Develop and manage Harness pipelines for continuous integration, continuous delivery, and automated deployments.
• Automate infrastructure provisioning using Terraform and Infrastructure as Code (IaC) practices.
• Work with containerization technologies such as Docker and Kubernetes.
• Deploy and manage applications on GCP services such as GKE, Compute Engine, Cloud Storage, and Cloud Run.
• Work with Azure services such as Azure Kubernetes Service (AKS), Azure Virtual Machines, Azure Storage, and Azure networking.
• Implement secure credential management, access controls, and cloud security best practices.
• Integrate automated testing, code quality checks, vulnerability scanning, and security gates into CI/CD pipelines.
• Monitor deployments, troubleshoot pipeline failures, and resolve build and release issues.
• Collaborate with development, QA, security, and infrastructure teams to improve deployment efficiency.
• Implement logging, monitoring, rollback strategies, and deployment governance.
• Support production releases, incident troubleshooting, and continuous improvement of DevOps processes.

Mandatory Skills

• Strong hands-on experience with GitHub Actions.
• Practical experience with Harness CI/CD.
• Good experience with GCP and Microsoft Azure cloud platforms.
• Strong understanding of CI/CD concepts, build automation, and release management.
• Experience with Git, branching strategies, pull requests, and version control.
• Scripting knowledge in Python, Bash, or PowerShell.
• Experience with Terraform or other Infrastructure as Code tools.
• Understanding of Docker and Kubernetes.
• Knowledge of cloud IAM, secrets management, networking, and security best practices.

We are seeking a highly skilled Senior DevOps Engineer with 8+ years of professional experience to join our team. In this role, you will design, implement, and optimize cloud infrastructure and CI/CD processes.

You will collaborate closely with development, QA, and operations teams to deliver scalable, secure, automated, and reliable solutions on AWS.

The ideal candidate will have strong hands-on experience with AWS, Terraform, Git/GitHub, Jenkins, PowerShell, Python, AWS Systems Manager (SSM) Documents, and Active Directory (AD) administration, along with a passion for automation, efficiency, and operational excellence.

Key Responsibilities

• Design, build, and maintain scalable cloud infrastructure on AWS.
• Develop and manage Infrastructure as Code (IaC) using Terraform.
• Build, maintain, and optimize CI/CD pipelines using Jenkins and GitHub.
• Use AWS Systems Manager (SSM) to support operational automation and system administration.
• Automate system tasks and administrative workflows using PowerShell and other scripting languages.
• Create, maintain, and execute custom SSM Documents for configuration management, patching, automation, and troubleshooting.
• Manage and administer Active Directory (AD), including users, groups, permissions, policies, authentication, and integration with AWS services.
• Implement and manage version-control workflows in Git and GitHub.
• Ensure infrastructure and deployment processes follow best practices for security, reliability, scalability, and cost optimization.
• Monitor and troubleshoot production systems to ensure high availability, performance, and reliability.
• Collaborate with development teams to improve software delivery processes and release management.
• Mentor junior engineers and contribute to the development of DevOps standards and best practices.

Required Skills and Experience

• 8+ years of professional experience, including at least 4 years in DevOps or Site Reliability Engineering (SRE) roles.
• Strong hands-on experience with AWS services, including EC2, VPC, IAM, S3, EKS, Lambda, and related services.
• Proven expertise in Terraform for Infrastructure as Code.
• Experience administering both Linux and Windows operating systems.
• Experience designing and managing CI/CD pipelines using Jenkins and GitHub.
• Proficiency with Git workflows and source-code management best practices.
• Strong PowerShell scripting skills; familiarity with Python and/or Bash is a plus.
• Experience with AWS Systems Manager (SSM), including creating and managing SSM Documents.
• Hands-on experience managing Active Directory, including users, groups, policies, authentication, permissions, and AWS integration.
• Solid understanding of cloud networking, security, monitoring, and troubleshooting.
• Excellent problem-solving, communication, collaboration, and decision-making skills.

Nice-to-Have Skills

• Experience with containerization and orchestration technologies, such as Docker, Kubernetes, and Amazon EKS.
• Knowledge of monitoring and observability tools, such as Amazon CloudWatch, New Relic, and Sumo Logic.
• An AWS certification, such as AWS Certified DevOps Engineer – Professional or AWS Certified Solutions Architect.

Who You Are

• You are eager to learn new technologies and continuously improve your skills.
• You make sound decisions and take ownership of your work.
• You are proactive, self-motivated, and comfortable taking initiative.
• You are a strong communicator who enjoys collaborating with cross-functional teams.
• You are committed to improving processes, automation, reliability, and operational efficiency.

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.

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

SIX-MONTH CONTRACT ONLY JOB: An engineer who prioritises infrastructure-as-code, with Terraform as the core skill, and delivers change through GitHub pipelines rather than manual intervention. Has a DevOps and automation mindset and applies zero-trust and least-privilege principles, designing access, secrets, and identity from the outset. Treats documentation as a key part of the build process and part of the definition of done, not an afterthought. Open and collaborative, building capability within the team so others can run and own what is delivered.

• Azure variant: strong Azure and Kubernetes experience.

• Snowflake variant: strong Snowflake operations experience, working alongside the DataOps team and applying the same infrastructure-as-code-first approach to the Snowflake environment.

Expected Skills:

• Infrastructure as Code: Strong hands-on Terraform experience, infrastructure provisioning and automated infrastructure management.

• CI/CD & Automation: GitHub Actions, secure pipeline implementation, multi-environment promotion and deployment automation.

• Security & Identity: Zero-trust principles, least-privilege access, secrets management, OIDC and Workload Identity Federation.

• Enterprise Networking: AKS-to-Snowflake and on-premises connectivity, private endpoints, Kubernetes network access controls and cross-boundary DNS resolution.

• Kubernetes Deployment & Administration: AKS/Kubernetes, Airflow or Dagster deployments, stateful workloads, resource isolation and dynamic worker autoscaling.

• Kubernetes Monitoring & Troubleshooting: Grafana, production issue diagnosis, pod memory leak detection, CPU/memory metrics and cluster bottleneck analysis.

• Snowflake IaC & Access Management: Terraform-based Snowflake provisioning, RBAC, role hierarchy and development, staging and production database permissions.

• Documentation & Ownership: Technical documentation, operational handover, collaborative working and team enablement.