DevOps & Cloud Engineering – AI Enabled Consultant

Harbinger Group; Pune District; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Harbinger Group is seeking a hands-on DevOps/Cloud Engineer in Pune for a Freelancer role. The candidate will automate software delivery, manage cloud infrastructure and improve reliability across AWS, Azure and GCP.

Strong CI/CD, IaC, containers, Kubernetes, monitoring, and DevSecOps are essential, with practical AI tooling experience desirable. The role requires 6–8 years of experience, expertise in one major cloud and working knowledge of others, plus strong security and networking

Qualifications

• 6–8 years of hands-on DevOps / Cloud experience.
• Strong experience in one major cloud – AWS / Azure / GCP.
• Working knowledge of at least one additional cloud.
• Terraform / Infrastructure as Code.
• Git / Git‑based workflows.
• Monitoring, logging and troubleshooting.
• Strong understanding of networking fundamentals.
• Security fundamentals / DevSecOps.
• Practical experience using AI coding/productivity tools.
• Understanding of AI‑assisted DevOps automation.
• Ability to use AI for troubleshooting, scripting and documentation while validating outputs.

Responsibilities

• Design, implement and maintain CI/CD pipelines using tools such as GitHub Actions, Azure DevOps, Jenkins or GitLab CI.
• Automate build, test, deployment and release processes.
• Implement branching, release and deployment strategies including blue‑green, canary and rolling deployments.
• Improve deployment reliability, speed and repeatability.
• Work hands‑on with AWS, Azure and/or GCP cloud environments.
• Provision and manage cloud infrastructure including compute, networking, storage, IAM and managed services.
• Understand equivalent services across cloud platforms and recommend appropriate solutions based on workload requirements.
• Support cloud migration, modernization and cost optimization initiatives.
• Develop reusable infrastructure using Terraform or equivalent IaC tools.
• Automate infrastructure provisioning, configuration and environment management.
• Implement infrastructure standards, reusable modules and automated policy controls.

Skills

DevOps experience

CI/CD workflows

Git/Git workflows

Networking fundamentals

Monitoring/logging

AI tools for DevOps

Security fundamentals

Tools

Terraform

Docker

Kubernetes

GitHub Actions

Azure DevOps

Jenkins

Argo CD

Job description

Baner, Pune, Maharashtra, India

6 - 8 Years

Consultant

Job Description

Experience - 6–8 years

Location- Pune

Mode- Freelancer

Role Overview

We are looking for a hands‑on DevOps / Cloud Engineer responsible for automating software delivery, managing cloud infrastructure, improving application reliability, and implementing secure, scalable cloud‑native environments across AWS, Azure and GCP.

The candidate should have strong hands‑on expertise in CI/CD, Infrastructure as Code, containers, Kubernetes, cloud services, monitoring and DevSecOps, along with practical experience using AI/GenAI tools to improve DevOps automation, troubleshooting and engineering productivity.

Required Skills

Must Have

• 6–8 years of hands‑on DevOps / Cloud experience
• Strong experience in one major cloud – AWS / Azure / GCP
• Working knowledge of at least one additional cloud
• Terraform / Infrastructure as Code
• Git / Git‑based workflows
• Monitoring, logging and troubleshooting
• Strong understanding of networking fundamentals
• Security fundamentals / DevSecOps

AI – Must Have

• Practical experience using AI coding/productivity tools
• Understanding of AI‑assisted DevOps automation
• Ability to use AI for troubleshooting, scripting and documentation while validating outputs

Good to Have

• AI agents / Agentic AI

Key Responsibilities

DevOps & CI/CD

• Design, implement and maintain CI/CD pipelines using tools such as GitHub Actions, Azure DevOps, Jenkins or GitLab CI.
• Automate build, test, deployment and release processes.
• Implement branching, release and deployment strategies including blue‑green, canary and rolling deployments.
• Improve deployment reliability, speed and repeatability.
• Work hands‑on with AWS, Azure and/or GCP cloud environments.
• Provision and manage cloud infrastructure including compute, networking, storage, IAM and managed services.
• Understand equivalent services across cloud platforms and recommend appropriate solutions based on workload requirements.
• Support cloud migration, modernization and cost optimization initiatives.

Important: one cloud experience is mandatory + working exposure to other cloud rather than deep expertise in all three.

Infrastructure as Code & Automation

• Develop reusable infrastructure using Terraform or equivalent IaC tools.
• Automate infrastructure provisioning, configuration and environment management.
• Implement infrastructure standards, reusable modules and automated policy controls.
• Maintain version‑controlled infrastructure and configuration.
• Build and manage Docker containers and containerised applications.
• Work with Kubernetes / EKS / AKS / GKE environments.
• Support deployments, scaling, configuration, secrets and troubleshooting.
• Exposure to Helm, GitOps and tools such as Argo CD is preferred.

DevSecOps

• Integrate security into CI/CD and infrastructure workflows.
• SAST
• DAST
• dependency scanning
• container/image scanning
• Follow secure cloud/IAM practices and support vulnerability remediation.

Observability & SRE

• Implement application and infrastructure monitoring, logging and alerting.
• Work with tools such as CloudWatch, Azure Monitor, GCP Operations Suite, Prometheus, Grafana, Datadog or OpenTelemetry.
• Support incident investigation, root‑cause analysis and performance troubleshooting.
• Contribute to reliability, availability and operational excellence.

AI‑Assisted DevOps

• Use AI tools such as GitHub Copilot, Amazon Q, Gemini, Claude or ChatGPT to improve:
• Infrastructure scripting
• documentation
• Demonstrate ability to validate and secure AI‑generated code/configuration rather than blindly accepting it.

AI is increasingly being incorporated into DevOps workflows for planning, coding, code review, security and operational troubleshooting.

AI / Agentic DevOps – Good to Have

• Exposure to AI agents / Agentic AI for IT operations.
• Understanding of how AI can support:
• incident triage
• root‑cause analysis
• automated remediation
• deployment analysis
• infrastructure monitoring
• Exposure to MCP (Model Context Protocol) or AI‑agent integration with DevOps tools is a plus.

AWS, for example, now provides AI‑powered DevOps capabilities that query infrastructure, metrics, alarms, deployments and incident patterns using natural language.

For stronger ATS-level candidates:

• Understanding of Platform Engineering / Internal Developer Platforms (IDP).
• Build reusable "Golden Paths" for development and deployment.
• Automate environment provisioning and developer self‑service.
• Exposure to Backstage or similar developer portals is a plus.

Platform engineering is increasingly being positioned as the layer that provides reusable, self‑service infrastructure, CI/CD and deployment capabilities to development teams.