Infrastructure Engineer

Job Title: Infrastructure Engineer
Location: Remote
Experience [10+] years

Must Have:
•    Terraform
•    CI/CD
•    GCP & Azure
•    Data & AI Platforms

About the Role:
•    We are looking for an experienced Infrastructure Engineer to design, automate, and operate scalable cloud infrastructure supporting data platforms and AI/ML workloads across GCP and Azure. This role focuses on Infrastructure such as Code, CI/CD automation, cloud networking, and enabling reliable, secure environments for data engineering and analytics teams.

Key Responsibilities:
•    Design, provision, and manage cloud infrastructure using Terraform
•    Build and maintain CI/CD pipelines using Azure DevOps
•    Provision and manage GCP infrastructure, including compute, storage, IAM, and networking
•    Support and manage Azure infrastructure (VNets, networking, compute, storage)
•    Design and implement network provisioning (VPC/VNet architecture, routing, firewalls, load balancers, private connectivity)
•    Build and operate infrastructure for data platforms (data lakes, warehouses, streaming, analytics platforms)
•    Provision and support AI/ML infrastructure, including GPU resources and AI platforms
•    Implement security best practices, IAM, encryption, and compliance controls
•    Optimize infrastructure for performance, reliability, and cost
•    Collaborate with data engineering, analytics, and ML teams
•    Document infrastructure, architecture, standards, and operational runbooks

Required Skills & Qualifications:
•    Strong experience with Terraform (Infrastructure as Code)
•    Experience with CI/CD pipelines, preferably Azure DevOps
•    Strong hands-on experience with Google Cloud Platform (GCP)
•    Solid understanding of cloud networking and network provisioning
•    Experience supporting data platforms or large-scale data workloads
•    Experience with AI/ML infrastructure
•    Strong Linux and scripting skills (Bash, Python, etc.)

Preferred / Nice to Have:
•    Hands-on experience with Azure infrastructure
•    Experience with Kubernetes (GKE / AKS)
•    Experience with data services such as BigQuery, Dataflow, Dataproc, Synapse, ADLS, Snowflake
•    Monitoring and observability tools (Prometheus, Grafana, Cloud Monitoring)
•    Multi-cloud experience and relevant certifications