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, setting 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: Robust 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 Qualified Cloud Architect or Professional DevOps/MLOps Engineer certifications

📌 Ai Platform Engineer Pune
🏢 Tvh India Private
📍 Pune