Cloud/DevOps Engineer

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Ekcel Technologies Inc, is seeking the following. Apply via Dice today!Job Title: Senior DevOps Engineer – AI/ML (12+ Years Experience)Job SummaryWe are looking for a highly experienced Senior DevOps Engineer with strong AI/ML exposure to design, build, and manage scalable, secure, and automated infrastructure supporting AI/ML workloads. The ideal candidate will have 12+ years of IT experience, deep DevOps expertise, and hands-on experience enabling machine learning and AI platforms in cloud environments.Key ResponsibilitiesDesign, implement, and maintain CI/CD pipelines for application and AI/ML model deployments.Build and manage cloud-native infrastructure to support AI/ML training, testing, and inference workloads.Automate infrastructure provisioning using Infrastructure as Code (Terraform, CloudFormation, ARM).Collaborate with Data Scientists and ML Engineers to productionize ML models (MLOps).Implement and manage containerization and orchestration using Docker and Kubernetes.Monitor, optimize, and troubleshoot system performance, availability, and scalability.Ensure security, compliance, and governance across DevOps and AI/ML platforms.Manage model versioning, data pipelines, and deployment workflows.Drive DevOps best practices and mentor junior engineers.Required Skills & Qualifications12+ years of overall IT experience with strong focus on DevOps engineering.Proven experience in DevOps tools: Jenkins, GitHub Actions, GitLab CI, Azure DevOps, etc.Strong hands-on experience with Cloud Platforms: AWS / Azure / Google Cloud Platform (AI/ML services preferred).Experience supporting AI/ML pipelines and MLOps frameworks (MLflow, Kubeflow, SageMaker, Azure ML, Vertex AI).Expertise in Docker, Kubernetes, and microservices architecture.Strong scripting skills in Python, Bash, or PowerShell.Experience with monitoring and logging tools (Prometheus, Grafana, ELK, CloudWatch, Azure Monitor).Solid understanding of Linux systems, networking, and security best practices.Nice to HaveExperience with GenAI, LLM deployments, or GPU-based workloads.Knowledge of data engineering pipelines (Airflow, Kafka).Certifications in AWS, Azure, Google Cloud Platform, or Kubernetes.Soft SkillsExcellent communication and stakeholder collaboration skills.Strong problem-solving and leadership abilities.Ability to work in fast-paced, enterprise environments.