DevOps Lead

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
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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 admin

Skills
Python, Git, Linux, AWS, Azure, Docker, Kubernetes

Experience
10+ yrs

Work arrangement
Yes