V
Systems Architect
V
Systems Architect
Virtusa- Posted an hour ago
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Job Description
Job Requirements
CLOUD AI SERVICES PRACTICE
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
1530years
CLOUD AI SERVICES PRACTICE
- 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
- 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)
- Google Cloud Generative AI Leader or Professional Machine Learning Engineer certification
- Experience with MLOps, CI/CD, and production model monitoring at scale
1530years
More Info
Key Skills
Production model monitoring
Gemini API
Claude
Vertex AI Search RAG Engine
Vertex AI Embeddings
Model Garden
Cloud Run
Retrieval-Augmented Generation (RAG)
Vertex AI
Gemma
Generative AI
Agent2Agent (A2A) protocol
MLOps automation
Model Armor
Agentic AI
Vertex AI Pipelines
Model Context Protocol (MCP)
Agent Development Kit (ADK)
Llama
CI/CD
Vertex AI Vector Search
About Company
