AI Platform Engineer

TVH Group; Pune District; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

TVH Group is seeking an experienced AI Infrastructure Engineer in Pune, India to architect and maintain cloud foundations for enterprise AI agents using Vertex AI Agent Builder. The role emphasizes IaC with Terraform, secure IAM governance, and robust CI/CD pipelines in GitLab.

You will ground agents on enterprise data, optimize runtimes, and monitor costs while ensuring scalable, secure infrastructure across GKE, Cloud Run, and related services.

Qualifications

• Hands-on experience with Vertex AI Agent Builder or Gemini Enterprise Agent Platform components.
• Advanced Terraform skills for modular, reusable code to manage IAM and cloud services.
• Proven CI/CD expertise with GitLab pipelines, runners, staging, caching and tests.
• Strong understanding of GCP baseline infrastructure (GKE, Cloud Run, VPC/Shared VPC, IAP, Cloud Storage).
• Programming skills in Python or Go for Agent ADK work.

Responsibilities

• Architect AI Agent Infrastructure and cloud foundations for enterprise AI agents.
• Maintain IaC declared via Terraform across all platform components.
• Design and optimize GitLab CI/CD pipelines for testing, deployment and pinning.
• Configure data ingestion pipelines to ground agents on enterprise data.
• Own IAM, service accounts, and agent identities for secure access.
• Implement observability, logging and cost monitoring for agent runtimes.

Skills

Vertex AI

Terraform

GitLab CI/CD

GKE

Cloud Run

IAP

Python

Go

IAM governance

Tools

Terraform

GitLab CI/CD

GKE

Cloud Run

IAP

Python

Go

Vertex AI Agent Builder

Job description

Key Responsibilities:

• Architect AI Agent Infrastructure: Design, provision, and maintain the cloud foundations required for enterprise AI agents using Vertex AI Agent Builder (Gemini Enterprise Agent Platform).
• Infrastructure as Code (IaC): Maintain a strict IaC philosophy, ensuring 100% of the platform’s infrastructure—from Agent Engine runtimes to VPCs and Cloud Storage Data Stores) is declared and managed via Terraform.
• Automate Everything: Build, optimize, and maintain robust, secure GitLab CI/CD pipelines for automated agent testing, deployment, and configuration pinning.
• Data & Grounding Management: Configure and optimize data ingestion pipelines (Vertex AI Search, Data Stores) to ground agents effectively on enterprise data.
• Security & IAM Governance: Own the complex IAM structures, Service Accounts, and cryptographic Agent Identities required to secure agent tool-calling and enterprise data access.
• Observability & Cost Optimization: Implement logging, monitoring, and tracing loops for agent reasoning, while keeping a sharp eye on token spend and runtime costs.

Core Technical Requirements Must-Haves

• GCP AI Ecosystem: Hands-on experience with Vertex AI Agent Builder (or Gemini Enterprise Agent Platform components like Agent Studio, Agent Development Kit (ADK), and Agent Engine).
• Advanced Terraform: Deep knowledge of writing reusable, modular Terraform code to manage complex cloud environments, IAM policies, and managed services.
• CI/CD Expertise: Proven track record of configuring complex GitLab pipelines, utilizing runners, environment staging, caching, and automated testing blocks.
• Core GCP Architecture: Solid understanding of baseline GCP infrastructure, including GKE, Cloud Run, VPC/Shared VPC networking, Identity-Aware Proxy (IAP), and Cloud Storage.
• Scripting & Orchestration: Strong programming skills in Python (preferred for Agent ADK work) or Go.

Nice-to-Haves

• Experience with LLM frameworks like LangChain, LlamaIndex, or Google's native Agent SDK.
• Familiarity with vector databases (Vertex AI Vector Search, Pinecone, or pgvector).
• GCP Professional Cloud Architect or Professional DevOps/MLOps Engineer certifications