Technical Specialist

Technology, Data & Digital · Technology and Services · Cloud Engineering · Data Science · DevOps

Smart Summary

AI-generated overview of this position

This role involves designing, deploying, and managing AI/ML workloads on Google Cloud Platform (GCP), building CI/CD pipelines, and containerizing services with Docker and Kubernetes. Key responsibilities include implementing MLOps/LLMOps practices and provisioning infrastructure using Terraform.

Job Summary

Design, deploy, and manage AI/ML workloads on Google Cloud Platform (GCP).

Build and maintain CI/CD pipelines for scalable AI and LLM applications.Containerize and orchestrate services using Docker and Kubernetes.

Implement MLOps / LLMOps practices for model deployment, versioning, and lifecycle management.

Provision and manage infrastructure using Terraform (IaC).

Support monitoring, security, governance, and cost optimization for AI platforms.

Key Responsibilities

Design, deploy, and operate scalable AI/ML platforms on Google Cloud Platform (GCP).

Build, automate, and maintain CI/CD pipelines for AI and LLM applications.Containerize applications and manage workloads using Docker and Kubernetes.

Implement and govern MLOps / LLMOps practices across model lifecycle (build, deploy, monitor).

Provision and manage cloud infrastructure using Terraform (Infrastructure as Code).

Enable monitoring, security, governance, and cost optimization for AI workloads.

Skill Requirements

Skill

Mandatory

Proficiency Level (1-5)

Cloud Platforms (GCP)

Must Have

5

CI/CD pipelines for AI applications

Must Have

5

Docker & Kubernetes

Must Have

5

MLOps / LLMOps

Must Have

5

Infrastructure as Code (Terraform)

Must Have

4

Monitoring & Observability

Good to Have

3–4

Security & Governance for AI systems

Good to Have

3–4

Cost optimization for AI workloads

Good to Have

3

Other Requirements

null

#AI/ML#GCP#CI/CD#Docker#Kubernetes#MLOps#LLMOps#Terraform#Infrastructure as Code#Monitoring#Security#Governance#Cost Optimization