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Vertex AIOps Platform Engineer (GCP)

Vertex AIOps Platform Engineer (GCP)

Prodapt Solutions

8 - 13 years

10 - 14 Lacs

bengaluru

Posted:2 weeks ago| Platform:

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Skills Required

gcp mlops python confluence google cloud platform cloud migration sre ai vpc automation iam cloud architecture cloud monitoring looker terraform ml engineer data lake

Work Mode

Work from Office

Job Type

Full Time

Job Description

Overview

The Lead AIOps Engineer is responsible for architecting, provisioning, and operationalizing multi-environment AI platforms on Google Cloud (Sandbox, Dev, Prod). The role includes cloud environment setup, IAM governance, CI/CD pipeline development, AIOps automation, drift detection, lifecycle process design, documentation, and alignment with broader enterprise platforms. This is a hands-on technical leadership position.

Responsibilities

Environment Provisioning

Conduct workshops to gather GCP environment requirements.
Design cloud architecture including VPC, IAM, subnetting, quotas, endpoints, and security controls.
Lead the provisioning of Sandbox, Dev, and Prod GCP projects using Terraform.
Oversee API enablement, configuration, and validation testing.

Role Definitions & IAM Governance

Define IAM roles for AI platform users (Owner, Support, ML Engineer, Viewer).
Create IAM matrices, RACI charts, and detailed access control documentation.
Ensure least-privilege access policies across Vertex AI and GCP services.
Coordinate reviews and approvals with security and architecture teams.

AIOps Framework Development

Design and implement drift detection, anomaly monitoring, canary releases, automated rollback, and observability components.
Build reusable CI/CD pipelines using Vertex Pipelines and Cloud Build.
Develop SOPs, diagrams, runbooks, and the full AIOps operations playbook.
Execute and validate synthetic drift, monitoring, and pipeline test scenarios.

Lifecycle Processes

Define the complete ML lifecycle from environment setup through deployment, monitoring, retraining triggers, and retirement.
Integrate lifecycle processes within CI/CD and AIOps automation.
Document all lifecycle flows in Confluence and conduct validation sessions.

Resource Planning & Cost Modelling

Develop team structure, roles, and support plans.
Build cost and usage models using GCP calculators and automation scripts.
Prepare development and production usage forecasts and long-term TCO estimates.

Alignment Analysis

Assess synergy with existing enterprise initiatives (Data Lake, Billing, Cloud Migration, Security).
Document dependencies, risks, and overlapping components.
Produce final recommendations and alignment reports.

Requirements

Core Technical Skills

Strong expertise in Google Cloud Platform: Vertex AI, IAM, VPC, Cloud Build, Cloud Run, Cloud Functions, Pub/Sub.
Deep experience with Terraform and Infrastructure as Code workflows.
Practical experience with AIOps and MLOps frameworks.
Proficient in Python for automation and monitoring jobs.
Experience designing and operating CI/CD pipelines for ML workloads.
Knowledge of observability tools such as Cloud Monitoring, Logging, and OpenTelemetry.

Soft Skills

Strong client-facing and stakeholder engagement abilities.
Experience leading engineering teams and driving architectural decisions.
Excellent documentation and presentation skills.
Ability to guide cross-functional teams through complex technical implementations.

Preferred Qualifications

GCP Professional ML Engineer or Cloud Architect certification.
Experience with Looker or other operational dashboards.
Background in ML engineering or SRE.

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Vertex AIOps Platform Engineer (GCP)