Overview
AI DevOps Engineer II responsible for developing, automating, and supporting cloud and AI/ML infrastructure, deployments, and operational workflows on AWS.
What you'll do
- Create and maintain automated product and AI/ML model deployments.
- Develop and support AWS components using Infrastructure as Code and automation.
- Implement AI-driven observability, predictive alerts, and self-healing solutions.
- Design AWS disaster recovery solutions covering backup, replication, and failover.
- Maintain CI/CD and MLOps pipelines using GitHub Workflows and Jenkins.
- Automate operations and API integrations with Python, Shell, and PowerShell.
- Manage end-to-end deployments and AI/ML infrastructure pipelines.
What you'll need
- 3–5 years of experience with monitoring and AIOps solutions.
- Experience with DevOps or MLOps in a large-scale enterprise environment.
- Proficiency with Docker, Kubernetes, ECS, EKS, and model-serving runtimes.
- Experience with AWS services including Backup, Elastic Disaster Recovery, and Lambda.
- Experience with Infrastructure as Code tools such as Terraform or CloudFormation.
- Strong Python knowledge and familiarity with AI/ML infrastructure components.
- Understanding of AI competencies including Agentic AI, RAG, MCP, custom skills, and LLMs.
Nice to have
- AWS Certified Solutions Architect or Certified DevOps Engineer certification.
- Monitoring tools setup experience with Datadog, Grafana, or similar tools.
- Hands-on experience with AI-assisted developer tools such as GitHub Copilot, Gemini, or Cursor.
Details
- Location: Chennai, India.
Read the full description and apply on the company’s own careers page.
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