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Job Title: AWS DevOps/MLOps Engineer (Agentic AI AWS) Experience: 6+ Years Location: Remote Budget: 1.10 LPM + GST Job Summary We are looking for an experienced AWS DevOps/MLOps Engineer to support an Agentic AI initiative. The ideal candidate should have strong hands-on experience with AWS infrastructure, DevOps automation, CI/CD, MLOps practices, and production deployment of AI/ML workloads. The candidate will be responsible for designing, automating, deploying, and maintaining scalable infrastructure and machine learning workflows on AWS. Key Responsibilities Design, provision, and manage scalable AWS infrastructure.Work with AWS services including:VPCEC2ECS / EKSS3IAMLambdaStep FunctionsImplement Infrastructure as Code using Terraform and/or AWS CloudFormation.Build and maintain CI/CD pipelines for AI/ML models, applications, and data pipelines.Implement end-to-end MLOps practices, including:Model and artifact versioningAutomated trainingAutomated testingModel deploymentModel monitoringWork with AWS SageMaker for model training, deployment, monitoring, and drift detection.Automate ML and data workflows using tools such as Airflow, AWS Step Functions, or Kubeflow.Build scalable deployment pipelines for Agentic AI and machine learning applications.Implement infrastructure and application monitoring using:AWS CloudWatchPrometheusGrafanaTroubleshoot infrastructure, deployment, and ML pipeline issues.Ensure AWS infrastructure follows security, scalability, reliability, and DevOps best practices.Mandatory Skills 6+ years of relevant DevOps / Cloud / MLOps experience.Strong hands-on experience with AWS.Experience with EC2, VPC, IAM, S3, Lambda, ECS and/or EKS.Strong knowledge of CI/CD pipeline development and automation.Hands-on experience with Terraform and/or CloudFormation.Experience implementing MLOps workflows.Hands-on experience with AWS SageMaker.Experience with model training, deployment, monitoring, and drift detection.Experience automating data/ML workflows using Airflow, Step Functions, or Kubeflow.Good understanding of containerization and orchestration.Experience with observability and monitoring tools such as CloudWatch, Prometheus, and Grafana.Strong troubleshooting and problem-solving skills.Preferred Skills Experience supporting Generative AI / Agentic AI workloads.Experience deploying AI/ML applications in production environments.Strong knowledge of Docker and Kubernetes.Experience managing scalable and secure cloud infrastructure.Understanding of model lifecycle management and production ML systems.Ideal Candidate We are looking for a hands-on AWS DevOps/MLOps Engineer who can independently build and manage cloud infrastructure, CI/CD pipelines, ML workflows, and production AI/ML deployments. Candidates with strong experience in AWS, SageMaker, Terraform, Kubernetes, CI/CD, MLOps, Airflow/Step Functions, and monitoring will be preferred. Interested candidates can share their updated resume at: hire@kasmoprav.com Email Subject: AWS DevOps/MLOps Engineer Agentic AI Compensation: 80,000.00 - 90,000.00 per month Work Location: Remote .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.