AI DevOps Engineer — Mid/Senior Level

<p><strong>Job Title: </strong>AI DevOps Engineer — Mid/Senior Level</p><p><strong>Experience:</strong> 4–7 Years</p><p><strong>Location:</strong> Raidurg Main Road, Hyderabad.</p><p><strong>Work Mode:</strong> On-site</p><p><strong>Work Hours:</strong> 2-11 PM</p><p><strong>Notice Period:</strong> Immediate Joiner (15-30 days)</p><p><br></p><p><strong>About us: </strong>At Stackular, we are more than just a team – we are a product development community driven by a shared vision. Our values shape who we are, what we do, and how we interact with our peers and our customers. We're not just seeking any regular engineer; we want individuals who identify with our core values and are passionate about software development.</p><p><br></p><p><strong>About the Role</strong></p><p>We are looking for a <strong>Mid-Level AI DevOps Engineer</strong> with <strong>4-7 years of experience</strong> in DevOps, cloud infrastructure, automation, and production deployment environments. This role will focus on building, maintaining, and improving scalable infrastructure and deployment pipelines for AI and machine learning applications.</p><p><br></p><p>The ideal candidate should have strong hands-on experience with <strong>cloud platforms, CI/CD, Docker, Kubernetes, infrastructure as code, monitoring, and automation</strong>, along with a working understanding of AI/ML deployment workflows.</p><p><br></p><p><strong>Key Responsibilities</strong></p><p><strong>Cloud Infrastructure & DevOps</strong></p><ul><li>Design, deploy, and manage cloud-based infrastructure for AI and software applications.</li><li>Work with cloud platforms such as <strong>AWS, Azure, or GCP</strong>.</li><li>Build and maintain infrastructure using tools such as <strong>Terraform, CloudFormation, Ansible</strong>.</li><li>Support scalable, secure, and reliable environments for production workloads.</li><li>Optimize infrastructure for performance, cost, availability, and operational efficiency.</li></ul><p><br></p><p><strong>CI/CD & Automation</strong></p><ul><li>Build and maintain CI/CD pipelines for application and AI service deployments.</li><li>Automate build, testing, deployment, and rollback processes.</li><li>Improve deployment reliability and reduce manual operational tasks.</li><li>Work with tools such as <strong>Azure DevOps, GitHub Actions, Jenkins</strong>.</li><li>Create reusable scripts, templates, and automation workflows for engineering teams.</li></ul><p><br></p><p><strong>Containerization & Orchestration</strong></p><ul><li>Deploy and manage containerized applications using <strong>Docker</strong>.</li><li>Work with <strong>Kubernetes</strong> for application deployment, scaling, networking, and troubleshooting.</li><li>Manage Helm charts and Kubernetes manifests.</li><li>Support production deployments and ensure application availability.</li><li>Troubleshoot container, cluster, and infrastructure-related issues.</li></ul><p><br></p><p><strong>AI / MLOps Support</strong></p><ul><li>Support deployment and monitoring of AI/ML models in production environments.</li><li>Collaborate with data scientists, ML engineers, and backend engineers to streamline model deployment workflows.</li><li>Assist with model versioning, model serving, and release automation.</li><li>Work with MLOps tools such as <strong>MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, Airflow, or similar platforms</strong>.</li><li>Support infrastructure for AI services, APIs, and model inference workloads.</li></ul><p><br></p><p><strong>Monitoring, Logging & Reliability</strong></p><ul><li>Implement and maintain monitoring, logging, tracing, and alerting systems.</li><li>Use tools such as <strong>Prometheus, Grafana, ELK Stack, Datadog, New Relic, CloudWatch, or Azure Monitor</strong>.</li><li>Monitor application and infrastructure performance.</li><li>Participate in incident response, root cause analysis, and production support.</li><li>Help improve system reliability, uptime, and operational visibility.</li></ul><p><br></p><p><strong>Security & Compliance</strong></p><ul><li>Apply DevSecOps practices across infrastructure and deployment pipelines.</li><li>Manage access controls, IAM roles, secrets, and secure configuration.</li><li>Support vulnerability scanning, patching, and security hardening.</li><li>Ensure cloud and deployment environments follow security best practices.</li><li>Work with tools such as <strong>HashiCorp Vault, AWS Secrets Manager, Azure Key Vault, or GCP Secret Manager</strong>.</li></ul><p><br></p><p><strong>Required Qualifications</strong></p><ul><li><strong>4-7 years of experience</strong> in DevOps, Cloud Engineering, Site Reliability Engineering, Platform Engineering, or Infrastructure Engineering.</li><li>Strong hands-on experience with at least one cloud platform: <strong>AWS, Azure, or GCP</strong>.</li><li>Experience building and managing CI/CD pipelines.</li><li>Strong proficiency on skills like <strong>Go, Python, Java, Ansible, Terraform, Pulumi, Shell Scripting, Bash, or PowerShell.</strong></li><li>Strong experience with <strong>Docker</strong> and containerized deployments.</li><li>Working experience with <strong>Kubernetes</strong> in production or near-production environments.</li><li>Experience with infrastructure-as-code tools such as <strong>Terraform, Ansible, CloudFormation</strong>.</li><li>Experience with monitoring and logging tools such as <strong>Prometheus, Grafana, ELK, Datadog, New Relic, or CloudWatch</strong>.</li><li>Good understanding of networking, Linux systems, security, and cloud architecture.</li><li>Familiarity with AI/ML workflows, model deployment, or MLOps concepts.</li><li>Experience supporting production applications and troubleshooting infrastructure issues.</li></ul><p><br></p><p><strong>Preferred Qualifications</strong></p><ul><li>Experience supporting AI/ML applications or model deployment pipelines.</li><li>Exposure to <strong>LLM applications, vector databases, RAG pipelines, or generative AI infrastructure</strong>.</li><li>Experience with GPU-based workloads or AI inference infrastructure.</li><li>Familiarity with tools such as <strong>MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, Airflow, or Argo Workflows</strong>.</li><li>Experience with Helm, service mesh, or Kubernetes operators.</li><li>Knowledge of DevSecOps practices and cloud security controls.</li><li>Cloud, Kubernetes, or DevOps certifications are a plus.</li></ul><p><br></p><p><strong>Required Technical Skills</strong></p><p><strong>Cloud Platforms:</strong> AWS, Azure, GCP</p><p><strong>Containers & Orchestration:</strong> Docker, Kubernetes, Helm</p><p><strong>Infrastructure as Code:</strong> Terraform, Ansible, CloudFormation</p><p><strong>CI/CD:</strong> GitHub Actions, Jenkins, Azure DevOps</p><p><strong>Scripting:</strong> Python, Bash, PowerShell</p><p><strong>Monitoring & Logging:</strong> Prometheus, Grafana, ELK Stack, Datadog, New Relic, CloudWatch</p><p><strong>MLOps / AI Tools:</strong> MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, Airflow</p><p><strong>Security:</strong> IAM, secrets management, vulnerability scanning, DevSecOps</p><p><strong>Operating Systems:</strong> Linux, Unix-based systems</p>

Back to blog

Other Jobs To Apply

No other job posts for this day.

Common Interview Questions And Answers

1. HOW DO YOU PLAN YOUR DAY?

This is what this question poses: When do you focus and start working seriously? What are the hours you work optimally? Are you a night owl? A morning bird? Remote teams can be made up of people working on different shifts and around the world, so you won't necessarily be stuck in the 9-5 schedule if it's not for you...

2. HOW DO YOU USE THE DIFFERENT COMMUNICATION TOOLS IN DIFFERENT SITUATIONS?

When you're working on a remote team, there's no way to chat in the hallway between meetings or catch up on the latest project during an office carpool. Therefore, virtual communication will be absolutely essential to get your work done...

3. WHAT IS "WORKING REMOTE" REALLY FOR YOU?

Many people want to work remotely because of the flexibility it allows. You can work anywhere and at any time of the day...

4. WHAT DO YOU NEED IN YOUR PHYSICAL WORKSPACE TO SUCCEED IN YOUR WORK?

With this question, companies are looking to see what equipment they may need to provide you with and to verify how aware you are of what remote working could mean for you physically and logistically...

5. HOW DO YOU PROCESS INFORMATION?

Several years ago, I was working in a team to plan a big event. My supervisor made us all work as a team before the big day. One of our activities has been to find out how each of us processes information...

6. HOW DO YOU MANAGE THE CALENDAR AND THE PROGRAM? WHICH APPLICATIONS / SYSTEM DO YOU USE?

Or you may receive even more specific questions, such as: What's on your calendar? Do you plan blocks of time to do certain types of work? Do you have an open calendar that everyone can see?...

7. HOW DO YOU ORGANIZE FILES, LINKS, AND TABS ON YOUR COMPUTER?

Just like your schedule, how you track files and other information is very important. After all, everything is digital!...

8. HOW TO PRIORITIZE WORK?

The day I watched Marie Forleo's film separating the important from the urgent, my life changed. Not all remote jobs start fast, but most of them are...

9. HOW DO YOU PREPARE FOR A MEETING AND PREPARE A MEETING? WHAT DO YOU SEE HAPPENING DURING THE MEETING?

Just as communication is essential when working remotely, so is organization. Because you won't have those opportunities in the elevator or a casual conversation in the lunchroom, you should take advantage of the little time you have in a video or phone conference...

10. HOW DO YOU USE TECHNOLOGY ON A DAILY BASIS, IN YOUR WORK AND FOR YOUR PLEASURE?

This is a great question because it shows your comfort level with technology, which is very important for a remote worker because you will be working with technology over time...