Senior Software Engineer -DevOps Engineer

Job Title: DevOps Engineer AI-Led Transformation
Position: Senior Software EngineerExperience:5- 8 YearsCategory: Software Development/ EngineeringShift: GeneralMain location: India - Bangalore, Hyderabad, Chennai, Mumbai, PunePosition ID: J0425-1152Employment Type: Full Time

Education Qualification: Bachelor's degree in computer science or related field or higher with minimum4 years of relevant experience.

Position Description: We are looking for a proactive and skilled Mid-Level DevOps Engineer to join our growing team and support cutting-edge AI-driven initiatives. This role is critical to building and maintaining scalable, reliable infrastructure for machine learning models and data-intensive applications. The ideal candidate will bring strong DevOps expertise, hands-on experience with cloud platforms, CI/CD, and a solid understanding of AI/ML workflows.

Your future duties and responsibilities
• Design and maintain CI/CD pipelines for AI/ML model training, testing, and deployment.• Manage cloud infrastructure (AWS, GCP, or Azure) optimized for AI workloads.• Automate infrastructure provisioning using Terraform, CloudFormation, or Ansible.• Support containerization (Docker) and orchestration (Kubernetes) of ML services.• Implement monitoring and alerting solutions (Prometheus, Grafana, ELK, Datadog).• Collaborate with AI teams to streamline workflows and ensure production readiness.• Ensure scalability, performance, and security across DevOps practices.• Troubleshoot infrastructure issues and conduct root cause analysis.

Required qualifications to be successful in this role
Must-Have:• 45 years in a DevOps role, preferably supporting AI/ML systems.• Experience with CI/CD tools (Jenkins, GitLab CI/CD, CircleCI).• Proficiency in Infrastructure as Code (Terraform, Ansible, CloudFormation).• Hands-on expertise with Docker and Kubernetes in production.• Cloud platform experience (AWS, GCP, or Azure).• Strong scripting skills (Bash, Python).• Familiarity with monitoring tools (Prometheus, Grafana, ELK Stack, or Datadog).

Good-to-Have:
• Experience with ML tools like MLflow, Kubeflow, SageMaker, or DVC.• Familiarity with AI/ML pipeline design and model versioning.• Understanding of security best practices in cloud DevOps environments.