Consultant: ATS DevOps & Cloud Engineering AI Enabled

Experience - 68 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 solid 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

68 years of hands-on DevOps / Cloud experience

Strong experience in one major cloud AWS / Azure / GCP

Working knowledge of at least one additional cloud

Strong CI/CD experience

Terraform / Infrastructure as Code

Docker

Kubernetes

Git / Git-based workflows

Linux

Scripting Python / Bash / PowerShell

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

AWS + Azure + GCP exposure

Helm

Argo CD / GitOps

Prometheus / Grafana / OpenTelemetry

Datadog

Backstage / IDP

Ansible

Vault / secrets management

FinOps / cloud cost optimization

AI agents / Agentic AI

MCP

MLOps / AI workload deployment

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.

Multi-Cloud Engineering





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.

Containers & Kubernetes

Build and manage Docker containers and containerized 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.

Implement

oSAST oDAST odependency scanning ocontainer/image scanning osecrets detection

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 / GenAI Expectations

AI-Assisted DevOps

Use AI tools such as GitHub Copilot, Amazon Q, Gemini, Claude or ChatGPT to improve:

oInfrastructure scripting oYAML/pipeline development oTerraform generation/review otroubleshooting olog analysis odocumentation otest automation

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:

oincident triage oroot-cause analysis oautomated remediation odeployment analysis ocloud resource optimization oinfrastructure 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 can query infrastructure, metrics, alarms, deployments and incident patterns using natural language.

Platform Engineering Preferred 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.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 DevOps & Cloud Engineering ? AI Enabled Consultant (Pune)
🏢 Harbinger Techventures
📍 Pune