Lead DevOps Engineer

Why Techjays

At Techjays, we're helping companies reimagine how they build, operate, and scale with AI at the core.

We're part of the small percentage of companies globally building secure, production-grade AI systems

that drive measurable business outcomes. Our team brings together engineers and leaders who have

built and scaled products at organizations like Google, NetApp, ADP, Cognizant Consulting, and

Capgemini.

We're looking for a DevOps Lead who can own cloud infrastructure, automation, CI/CD, reliability and

engineering practices for modern software and AI-enabled platforms. The ideal candidate will be deeply

specialized in either AWS or Azure, with strong hands-on DevOps experience and practical exposure to

AI workloads or AI-driven products.

Key Skills

Cloud Technologies (Expert): Strong hands-on expertise in either AWS or Azure. Deep practical

experience designing, deploying and operating production cloud environments.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch and related infrastructure services.

Azure: Azure VMs, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault and

related infrastructure services.

CI/CD: Azure DevOps, GitHub Actions, Jenkins, GitLab CI or equivalent, including multi-stage pipelines,

approvals, artifact management and deployment automation.

Containers & Kubernetes: Docker, Kubernetes, AKS or EKS, Helm, scaling, networking, secrets and

production workload management.

Infrastructure as Code: Strong Terraform experience preferred. Exposure to CloudFormation, Bicep,

ARM or similar IaC tools is valuable.

Automation & Scripting: Strong Python, Bash and/or PowerShell skills for infrastructure automation,

deployment and operational tooling.

Monitoring & Reliability: CloudWatch, Azure Monitor, Prometheus, Grafana, centralized logging,

alerting, incident management and performance optimization.

AI Exposure: Prior experience supporting AI/ML applications, GenAI platforms, AI services, LLM

applications or AI-enabled products. This is an exposure requirement, not an MLOps-specialist role.

Roles & Responsibilities

• Lead the design, implementation and operation of scalable, secure and highly available cloud
  
  

infrastructure.

• Own DevOps strategy and technical direction across cloud infrastructure, CI/CD, automation and
  
  

production operations.

• Build and maintain CI/CD pipelines for application and AI-enabled workloads across development,
  
  

staging and production.

• Design and manage Kubernetes environments using AKS, EKS, Docker and Helm.
• Implement Infrastructure as Code using Terraform and relevant cloud-native tools.
• Establish deployment standards, reusable pipeline templates and automated release processes.
• Implement monitoring, logging, alerting and operational practices to maintain reliability and
  
  

performance.

• Work closely with engineering and AI teams to provide the infrastructure required to deploy and
  
  

operate AI-enabled applications.

• Support cloud environments used by AI/ML applications, including compute, networking, containers,
  
  

storage, security and observability.

• Drive cloud security practices covering IAM/RBAC, secrets, networking, access controls and
  
  

infrastructure governance.

• Troubleshoot complex production issues, lead RCA and implement permanent fixes through
  
  

automation and engineering improvements.

• Optimize infrastructure performance and cloud costs while maintaining reliability and scalability.
• Evaluate and introduce DevOps tools and practices that improve engineering productivity and
  
  

deployment quality.

• Mentor DevOps engineers and provide technical leadership across projects and teams.
  
  

What We're Looking For Beyond Skills

• Cloud specialist: Deep hands-on expertise in either AWS or Azure. You do not need to be an expert in
  
  

both.

• Strong DevOps foundation: Proven experience owning CI/CD, cloud infrastructure, containers,
  
  

automation and production operations.

• AI exposure: You have worked with or supported AI/ML, GenAI, LLM or AI-enabled applications and
  
  

understand their infrastructure needs.

• Builder mindset: You can design, implement and improve systems rather than only manage existing
  
  

environments.

• Ownership: You take responsibility for reliability, delivery, security and operational excellence.
• Leadership: You can mentor engineers, drive technical decisions and work effectively with
  
  

engineering and product teams.

• Location & availability: Willing to work onsite from the Coimbatore office and available to join
  
  

immediately / at short notice.

Good to Have

• Experience supporting AI/ML, Generative AI, LLM or AI-agent based applications in production.
• Experience with GitOps and Argo CD.
• Experience with cloud security, governance, networking and enterprise landing zones.
• Experience with blue/green, canary and automated rollback strategies.
• Experience with Python-based automation or AI integrations.
• Experience with FinOps and optimization of cloud infrastructure costs.
• Relevant AWS, Azure or Kubernetes certifications.
  
  

What We Offer

• Competitive compensation
• Coimbatore office-based role with a strong engineering environment
• Opportunity to lead production-grade cloud and AI-enabled platforms for global clients
• Exposure to modern AWS/Azure, Kubernetes, DevOps and AI engineering practices
• Paid holidays & flexible time off
• Medical insurance (Self & Family, up to 4 Lakhs per person)
• A culture that values clarity, integrity and continuous growth