CLOUD AI SERVICES PRACTICE

GOOGLE CLOUD

Cloud AI Engineer — Agentic AI & Generative AI (Google Cloud)

Experience: 15+ years

We are looking for a senior engineer with 7—10 years of overall software/ML engineering experience, including at least 3 years building Agentic AI and Generative AI solutions on Google Cloud, to design, build, and deploy production-grade agentic and GenAI systems across the full AI stack.

Responsibilities

Architect and build GenAI solutions using Vertex AI and Gemini, selecting models via Model Garden (Gemini, Claude, Gemma, Llama)
Design and own Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Embeddings, Vertex AI Vector Search, and Vertex AI Search / RAG Engine
Lead development of production AI agents using the Agent Development Kit (ADK) on Vertex AI Agent Engine, with tool-calling via the Model Context Protocol (MCP) and multi-agent coordination via the Agent2Agent (A2A) protocol
Define and enforce safety guardrails (Model Armor) and lead agent/GenAI evaluation before production release
Own MLOps automation with Vertex AI Pipelines and drive tuning of Gemini and other models
Mentor engineers and guide architecture decisions for agentic AI adoption across teams

Required Skills

15+ years overall software/ML engineering experience, including at least 3 years hands-on with Agentic AI and Generative AI specifically
Deep hands-on experience with Vertex AI and/or the Gemini API in a production environment
Strong grasp of embeddings, vector search, and Retrieval-Augmented Generation (RAG) architecture
Practical experience with ADK, MCP tool-calling, and A2A multi-agent patterns
Strong Python and Google Cloud fundamentals (Cloud Storage, IAM, Cloud Run)

Preferred

Google Cloud Generative AI Leader or Professional Machine Learning Engineer certification
Experience with MLOps, CI/CD, and production model monitoring at scale

Systems Architect