Google AI Architect

InfoVision Inc.; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

InfoVision Inc. seeks an Enterprise AI Architect to define and lead the AI architecture strategy, leveraging Google Gemini Enterprise, Vertex AI and production-grade agentic AI solutions for telecom use cases.

You will design multi-agent systems, establish governance, and drive integration with OSS/BSS platforms while mentoring architects and overseeing AI innovation discussions.

Qualifications

• 15+ years of IT experience with architecture focus.
• 7+ years in enterprise architecture and large-scale design.
• 5+ years in AI/ML, Generative AI and cloud AI platforms.
• Hands-on with Google Gemini Enterprise and Vertex AI.

Responsibilities

• Define and lead the enterprise AI architecture strategy utilizing Google Gemini Enterprise, Vertex AI, and related services.
• Design scalable, secure, and production-grade Agentic AI solutions for telecom use cases.
• Architect multi-agent systems with reasoning, planning, orchestration, and autonomous decision-making.
• Establish AI governance, reference architectures, and best practices across the organization.

Skills

Enterprise architecture

AI/ML

Generative AI

Google Gemini Enterprise

Vertex AI

LLMs

Prompt engineering

Python

API integrations

Team leadership

Tools

LangGraph

CrewAI

AutoGen

Semantic Kernel

Google ADK

MCP

Job description

• Define and lead the enterprise AI architecture strategy leveraging Google Cloud AI services, Gemini Enterprise, and Vertex AI.
• Design scalable, secure, and production-grade Agentic AI solutions for telecom use cases.
• Architect multi-agent systems capable of reasoning, planning, orchestration, and autonomous decision-making.
• Establish AI reference architectures, governance models, and best practices across the organization.

Gemini Enterprise & Agentic AI

• Design and deploy enterprise AI assistants and autonomous agents using Gemini Enterprise.
• Build Agentic AI ecosystems leveraging frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, ADK, or similar technologies.
• Develop Retrieval-Augmented Generation (RAG) architectures using structured and unstructured enterprise data.
• Implement memory management, tool calling, agent orchestration, and workflow automation capabilities.
• Leverage deep telecom domain expertise to build AI solutions for:
• Fault prediction and root-cause analysis
• Service assurance and network optimization
• Capacity planning and traffic engineering
• Customer experience analytics
• Telecom inventory and provisioning automation
• Collaborate with network engineering teams to integrate AI capabilities into telecom operations platforms.
• Integrate AI solutions with OSS/BSS systems, network monitoring platforms, ITSM tools, and enterprise applications.
• Design API-driven architectures supporting real-time and batch processing.
• Implement secure AI access controls, governance, observability, and compliance frameworks.
• Serve as the technical authority for AI architecture decisions.
• Mentor architects, AI engineers, and data scientists.
• Drive AI strategy workshops and executive discussions.
• Evaluate emerging AI technologies and establish AI innovation roadmaps.

Required Qualifications

• 15+ years of overall IT experience.
• 7+ years in enterprise architecture and large-scale solution design.
• 5+ years in AI/ML, Generative AI, and cloud AI platforms.
• Hands‑on experience with Google Gemini Enterprise and Vertex AI.
• Proven expertise in Agentic AI architecture and implementation.
• Deep understanding of LLMs, RAG, prompt engineering, vector databases, and AI orchestration frameworks.
• Strong programming experience in Python and API‑based integrations.

Strong experience in one or more of the following:

• Telecom Service Providers
• IP/MPLS Networks
• Optical Transport Networks
• SD‑WAN
• Network Operations & Service Assurance
• OSS/BSS Platforms
• Network Automation
• Telecom Analytics
• Capacity Planning & Performance Engineering

Preferred experience with companies such as Zayo, Lumen, Verizon, AT&T, Comcast, Cox, Frontier, Charter, or equivalent telecom/network infrastructure organizations.

Technical Skills

• Agent Builder
• Google AI Studio
• BigQuery
• Dataflow
• GKE
• Pub/Sub
• Cloud Functions

Agentic AI & GenAI

• LangGraph
• CrewAI
• AutoGen
• Semantic Kernel
• Google ADK
• MCP
• Multi‑Agent Systems
• RAG
• Prompt Engineering

Data & AI

• Knowledge Graphs
• Neo4j
• MLflow
• LLMOps
• MLOps

Programming

• Python
• REST APIs
• FastAPI
• SQL
• Terraform
• Docker

Preferred Certifications

• Google Professional Cloud Architect
• Google Professional Machine Learning Engineer
• Google Generative AI Certifications
• TOGAF Certification
• AI/ML Architecture Certifications

What Makes You Successful

• Ability to translate telecom business challenges into AI‑powered solutions.
• Strong executive communication and stakeholder management skills.
• Deep hands‑on architecture experience, not just strategy.
• Proven track record of delivering enterprise AI initiatives from concept to production.