Overview
AI Operations Engineer responsible for building, automating, securing, and operating cloud and AI infrastructure for production artificial intelligence solutions.
What you'll do
- Operate cloud infrastructure for AI workloads across compute, storage, networking, and security.
- Build MLOps and LLMOps pipelines for model deployment, versioning, evaluation, and monitoring.
- Design CI/CD pipelines for front-end, back-end, and AI components.
- Manage Infrastructure as Code using Terraform, Cloud Build, and Kubernetes manifests.
- Operate Docker and Kubernetes microservices, including scaling and rolling deployments.
- Implement monitoring, logging, tracing, alerting, and SRE practices.
- Provide self-service tooling and automated workflows for engineering and analytics teams.
What you'll need
- Bachelor's or Master's degree in a specified technical discipline.
- 3–5 years of cloud engineering, DevOps, or SRE experience.
- 1–2 years of hands-on experience operating AI, ML, or Generative AI applications in production.
- Experience with Docker, Kubernetes, Terraform, Cloud Build, and GKE.
- Hands-on experience with Google Cloud services including Cloud Run, GCS, BigQuery, IAM, VPC networking, and Secret Manager.
- Python or Bash scripting experience for infrastructure automation.
- Knowledge of cloud security, access management, secrets management, and compliance.
Nice to have
- Experience in integrated marketing, digital agency, marketing services, or consulting environments.
- Exposure to banking, financial services, or credit analytics.
- Machine Learning engineering or model serving framework experience.
- Relevant Google Cloud certifications.
Details
- Location: Chennai, India.
Read the full description and apply on the company’s own careers page.
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