AI Engineer 4A

Overview

Support the DevOps, MLOps, and LLMOps infrastructure used to deploy and operate generative AI and agentic AI applications. This hands-on individual contributor role works with senior AI engineers and DevOps managers across hybrid and multi-cloud environments.

What you'll do

• Build and maintain CI/CD pipelines for applications and model deployments.
• Package applications with Docker and support Kubernetes operations.
• Write Infrastructure as Code for cloud resource provisioning.
• Support model-serving and GenAI application deployments.
• Set up monitoring, logging, and alerting and troubleshoot production issues.
• Support vulnerability scanning, patching, and secrets management.
• Maintain runbooks, deployment guides, and automation documentation.

What you'll need

• At least 2 years of hands-on DevOps, infrastructure, or site reliability engineering experience.
• Python and/or Bash scripting skills with working knowledge of Ansible.
• Experience with at least two listed CI/CD tools.
• Practical Docker and Kubernetes experience, including Helm charts.
• Working knowledge of Terraform and/or CloudFormation.
• Experience with at least one of AWS, Azure, or GCP.
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.

Nice to have

• Exposure to GenAI, LLM, agentic AI, vector databases, DevSecOps, GitOps, service mesh, or FinOps tools and practices.
• Prior experience in a data science or applied AI environment.
• Relevant cloud, Kubernetes, or Terraform certifications.
• AI/ML publications, patents, or open-source contributions.

Details

• Hybrid work mode.
• Day shift in India.
• Regular employment type.
• Location: Bangalore, Karnataka, India.