Enterprise Architect - Agentic AI/CRM &BPM

Position: Enterprise Architect – Agentic AI / CRM & BPM – 15+yrs overall experience
Location: Las Vegas, NV (On-site from day1)

Duration: Long term

Role Overview

We are looking for a senior Enterprise/AI Architect with hands-on experience designing Agentic AI / Generative AI solutions for CRM and BPM environments.

The candidate should have strong Google Cloud (Google Cloud Platform) AI/ML expertise, experience building autonomous or multi-agent systems, and the ability to integrate AI agents across the software development and testing lifecycle.

Key Responsibilities

·       Architect and design Agentic AI solutions for CRM and BPM platforms across the SDLC — from requirements → backlog → development → testing → deployment.

·       Design and lead development of autonomous AI agents capable of reasoning, decision-making, collaboration, and task execution across the software testing lifecycle.

·       Build and optimize AI/ML pipelines using Google Cloud Platform, particularly Vertex AI, BigQuery, Cloud Functions, and related services.

·       Integrate AI agents with CI/CD pipelines, test management tools, test automation frameworks, and developer environments.

·       Deploy and orchestrate AI agents using Google AgentSpace or comparable agent orchestration platforms.

·       Design multi-agent workflows and establish patterns for agent communication, lifecycle management, scalability, and monitoring.

·       Work closely with QA, DevOps, Product Engineering, and business stakeholders to identify and implement AI-driven automation opportunities.

·       Establish standards for AI safety, governance, interpretability, observability, security, and performance.

·       Evaluate emerging technologies in LLMs, Generative AI, multi-agent systems, and autonomous software engineering.

·       Provide architecture guidance, technical leadership, design documentation, and best practices to engineering teams.

Required Qualifications – Must Have

1.     Agentic / Generative AI

·       Proven experience as an AI Architect, ML Engineer, Solution Architect, or Enterprise Architect.

·       2+ years of hands-on AI/ML experience, including 1+ year focused on Generative AI / Agentic AI.

·       Hands-on experience designing or implementing AI agents, autonomous workflows, or multi-agent systems.

·       Strong understanding of LLMs, RAG, prompt engineering, tool/function calling, agent orchestration, and multi-agent architectures.

2.     Google Cloud Platform / Google AI

·       Strong hands-on Google Cloud Platform experience, particularly within the AI/ML ecosystem.

·       Experience with Vertex AI, BigQuery, Cloud Functions, and related Google Cloud Platform services.

·       Experience building, deploying, or managing AI solutions on Google Cloud Platform.

3.     CRM & BPM

·       3+ years of hands-on experience developing or working with CRM and BPM solutions.

·       Ability to understand and architect AI use cases within enterprise CRM/BPM workflows.

4.     Testing & SDLC

·       Strong understanding of the software development and testing lifecycle.

·       Experience with test automation frameworks/tools such as Selenium, TestNG, JUnit, or equivalent.

·       Experience integrating AI agents into QA/testing and CI/CD processes.

5.     Agent Deployment / Orchestration

·       Experience deploying and managing agents using Google AgentSpace or a comparable agent orchestration/agent platform.

·       Understanding of agent lifecycle management, communication, scalability, monitoring, and governance.

6.     Architecture & Leadership

·       Strong enterprise architecture and solution-design experience.

·       Excellent communication, problem-solving, stakeholder-management, and technical leadership skills.

Nice to Have

·       Direct experience with Google AgentSpace.

·       Experience with Gemini / Vertex AI Agent Builder / Agent Engine.

·       Salesforce, Microsoft Dynamics, Pega, Appian, Camunda, or similar CRM/BPM platforms.

·       Experience building AI-powered software testing or autonomous QA agents.

·       Experience with AI governance, evaluation frameworks, safety, and responsible AI.

·       Experience designing enterprise-scale multi-agent architectures.