Senior Tech S and T - Network Engineer

Jobtailor; Bengaluru; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Jobtailor in Bengaluru, Karnataka, seeks a seasoned DevOps/AI infra engineer to build secure CI/CD pipelines for application, data, and AI workloads. You will implement shift-left security, SBOM automation, and policy-as-code while deploying containerized workloads on Kubernetes with Helm/Kustomize.

You will develop MLOps workflows for model training, packaging, and deployment, integrate RAG/AI pipelines, and ensure observability, governance, and compliance across GDPR/CCPA standards.

Qualifications

• Hands-on experience in cloud, DevOps, and AI/ML workflows.

Responsibilities

• Build and maintain secure CI/CD pipelines for application, data, and AI workloads
• Integrate DevSecOps practices and continuous security scanning into pipelines
• Implement shift-left security with secret scanning, SBOM automation, and dependency management
• Deploy containerized workloads on Kubernetes using Helm/Kustomize and secure image pipelines
• Develop and automate MLOps workflows for model training, packaging, and deployment
• Build RAG/AI integration pipelines using LLM orchestration tools and vector databases
• Implement scalable AI inference and model-serving systems
• Automate ETL/ELT and data-feature pipelines for AI model data feeds
• Provision cloud and AI infrastructure using Infrastructure as Code
• Implement event-driven architectures with serverless functions and messaging systems
• Maintain monitoring, logging, and model/data observability for application and ML workloads
• Secure cloud environments using IAM, workload identities, and least-privilege controls
• Support configuration management and environment automation
• Develop Python, Bash, or SQL scripts for automation, data processing, validation, and ML workflow orchestration
• Implement REST, gRPC, or GraphQL API integrations for AI systems
• Use GitOps tools for secure Kubernetes deployments and progressive delivery
• Apply AI security practices including guardrails, prompt protection, model validation, and safe inference
• Ensure compliance with GDPR, CCPA, data governance, privacy, and security standards
• Collaborate with data engineers, ML engineers, DevOps teams, and security teams; contribute to documentation, reviews, and mentoring

Skills

CI/CD Pipeline Development

DevSecOps Implementation

MLOps Workflow Automation

Kubernetes Deployment

Infrastructure as Code

Python

Shell Scripting

Cloud Platforms

Education

B.Tech./BS in Computer Science

Tools

Terraform

Kubernetes

Helm

Docker

GitHub Actions

GitLab CI

Jenkins

Azure DevOps

Job description

• Build and maintain secure CI/CD pipelines for application, data, and AI workloads
• Integrate DevSecOps practices and continuous security scanning into pipelines
• Implement shift-left security with secret scanning, SBOM automation, and dependency management
• Deploy containerized workloads on Kubernetes using Helm/Kustomize and secure image pipelines
• Develop and automate MLOps workflows for model training, packaging, and deployment
• Build RAG/AI integration pipelines using LLM orchestration tools and vector databases
• Implement scalable AI inference and model-serving systems
• Automate ETL/ELT and data-feature pipelines for AI model data feeds
• Provision cloud and AI infrastructure using Infrastructure as Code
• Implement event-driven architectures with serverless functions and messaging systems
• Maintain monitoring, logging, and model/data observability for application and ML workloads
• Secure cloud environments using IAM, workload identities, and least-privilege controls
• Support configuration management and environment automation
• Develop Python, Bash, or SQL scripts for automation, data processing, validation, and ML workflow orchestration
• Implement REST, gRPC, or GraphQL API integrations for AI systems
• Use GitOps tools for secure Kubernetes deployments and progressive delivery
• Apply AI security practices including guardrails, prompt protection, model validation, and safe inference
• Ensure compliance with GDPR, CCPA, data governance, privacy, and security standards
• Collaborate with data engineers, ML engineers, DevOps teams, and security teams; contribute to documentation, reviews, and mentoring

Requirements

• 4–7 years of hands-on experience in cloud, DevOps, and AI/ML workflows
• Strong skills in Terraform, Kubernetes, Helm, Docker, and CI/CD tools including GitHub Actions, GitLab CI, Jenkins, and Azure DevOps
• Proficiency in Python and scripting with Bash/PowerShell
• Experience implementing DevSecOps practices including SAST/DAST, container scanning, secrets scanning, SBOM, and policy-as-code
• Exposure to MLOps/AI integration using MLflow, Kubeflow, SageMaker, Azure ML, KServe, or Seldon
• Familiarity with AWS, Azure, or GCP; Ansible/Puppet; and Argo CD/Flux
• Strong communication, troubleshooting, and collaboration skills with ability to work cross-functionally
• B.Tech. / BS in Computer Science
• Knowledge of Terraform, Pulumi, Infrastructure as Code, Kubernetes, Docker/Podman, Helm, Kustomize, CI/CD, AWS/Azure/GCP, Python, Bash, PowerShell, DevSecOps tools, policy-as-code, SBOM, MLOps, model serving, vector databases, RAG, monitoring, observability, configuration management, GitOps, and serverless technologies

Core Competencies

Demonstrates expertise in building and maintaining secure CI/CD pipelines, integrating DevSecOps practices, and automating MLOps workflows. Proficient in cloud infrastructure provisioning and implementing scalable AI systems while ensuring compliance with data governance and security standards.

Highest-signal resume keywords

• CI/CD Pipeline Development
• DevSecOps Implementation
• MLOps Workflow Automation
• Kubernetes Deployment
• Infrastructure as Code

Hard Skills

• Terraform
• Kubernetes
• Python
• Bash
• Docker
• CI/CD Tools
• MLOps
• DevSecOps Tools
• API Integration
• Event-Driven Architecture

Soft Skills

• Strong Communication
• Troubleshooting
• Collaboration

Certifications & Qualifications

• B.Tech.
• BS in Computer Science

Industry Keywords

• DevSecOps
• GDPR
• CCPA
• Data Governance
• Security Standards
• Monitoring
• Observability
• Configuration Management
• Serverless Technologies
• Policy-as-Code

Tools & Technologies

• GitHub Actions
• GitLab CI
• Jenkins
• Azure DevOps
• MLflow
• Kubeflow
• SageMaker
• AWS
• Azure
• GCP