DevOps Engineer (AI/ML Platform) - Job Description

Job Title: DevOps Engineer - AI/ML Platform
Experience: 10+ years

About the Role

Key Responsibilities-
Automate infrastructure provisioning using Infrastructure as Code (IaC) tools.
Deploy and manage containerized workloads using Kubernetes.
Implement MLOps workflows for model training, validation, deployment, and monitoring.
Optimize cloud resources for performance, scalability, and cost efficiency.
Monitor platform health, troubleshoot production issues, and ensure high availability.
Implement security best practices, including secrets management, IAM, and compliance controls.
Collaborate with data scientists, ML engineers, software developers, and platform teams.
Establish observability solutions using logging, monitoring, and tracing tools.

Required Skills:
DevOps & Cloud
Solid experience with at least one major cloud platform:
Amazon Web Services (AWS)
Microsoft (Azure)
Google (GCP)
Expertise in Linux system administration.
Experience with containerization technologies such as:
Docker




Kubernetes
Solid knowledge of Infrastructure as Code:
Terraform
Ansible
CI/CD tools such as:
Jenkins
GitHub Actions
GitLab CI/CD

AI / MLOps
Experience supporting AI/ML workloads in production.
Knowledge of MLOps frameworks and tools:
MLflow
Kubeflow
Experience with model deployment, model serving, and monitoring.
Understanding of GPU-based infrastructure and distributed training environments.- Experience integrating AI services and APIs.

Monitoring & Security
Monitoring and observability:
Prometheus
Grafana
OpenTelemetry
Security and secrets management:
HashiCorp Vault
Knowledge of DevSecOps practices.

Preferred Qualifications
Experience with Large Language Models (LLMs) and Generative AI platforms.
Experience with Retrieval-Augmented Generation (RAG) architectures.
Certifications in AWS, Azure, GCP, Kubernetes, or Terraform.
Experience managi

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