Agentic AI Architect-Google Cloud

West Monroe•Washington, DC

2h•$163,100 - $220,700•Hybrid

About The Position

West Monroe is seeking an experienced Agentic AI Architect to join our Technology & Experience (TechEx) practice within the Software discipline. This highly client-facing role will lead the strategy, architecture, and engineering delivery of enterprise agentic AI solutions, with Google Cloud serving as the individual’s primary area of specialization. The architect will work directly with technology executives, business leaders, enterprise architects, and engineering teams to translate business objectives into secure, scalable, and production-ready AI solutions. The role requires an individual who can communicate complex technical concepts clearly, facilitate architecture decisions, establish trusted client relationships, and lead multidisciplinary teams of software, platform, data, AI, and quality engineers. This role combines enterprise AI strategy, executive advisory, deep software engineering, and delivery leadership to help clients move from experimentation to production-scale agentic AI. The Architect will define target architectures and operating models for secure, governed AI platforms centered on Google Cloud and the Gemini Enterprise Agent Platform, including Vertex AI, Gemini, Agent Development Kit (ADK), Agent Engine, Retrieval-Augmented Generation (RAG), and cloud-native services. The ideal candidate brings hands-on credibility across distributed systems, platform engineering, AI security, governance, and production operations, and can lead multidisciplinary teams through modernization and measurable business outcomes.

Requirements

8+ years of experience in software engineering, cloud architecture, or platform engineering designing and delivering enterprise applications.
3+ years of experience architecting and implementing solutions on Google Cloud Platform.
Strong software engineering background with proficiency in Java, Python, Go, or TypeScript and experience building distributed systems, APIs, and microservices.
Hands-on experience with Vertex AI, Gemini APIs, Agent Development Kit (ADK), Agent Engine, Vertex AI Search, Vector Search, or comparable generative AI platforms.
Experience designing or implementing agentic AI solutions, multi-agent orchestration, tool calling, prompt engineering, Retrieval-Augmented Generation (RAG), and enterprise AI application architectures.
Experience with Kubernetes, Docker, Google Kubernetes Engine (GKE), Cloud Run, Terraform, GitHub Actions or Cloud Build, CI/CD pipelines, and DevSecOps practices.
Knowledge of cloud networking, IAM, security, observability, reliability engineering, and enterprise platform governance.
Experience integrating enterprise data platforms, APIs, vector databases, knowledge retrieval systems, and AI services into scalable software solutions.
Understanding of Responsible AI principles, model evaluation, AI governance, and secure deployment of production AI systems.
Experience integrating AI tools (e.g., ChatGPT) into day-to-day workflows to enhance productivity and insight generation, coupled with strong critical thinking to assess accuracy, mitigate bias, and ensure high-quality outputs.
Strong communication and consulting skills with the ability to explain complex technical concepts to engineering teams, architects, and executive stakeholders.
Ability to travel 25 to 50%.
A commitment to inclusion and diversity, and openness to new ideas and perspectives.
Ability to work permanently in the United States without sponsorship.

Nice To Haves

Google Cloud Professional Cloud Architect certification preferred.
Professional Machine Learning Engineer, Generative AI Leader, or Generative AI Engineer certifications are a plus.

Responsibilities

Serve as the AI architecture and technical delivery lead, partnering with client executives to translate business strategy into a prioritized Google Cloud roadmap, target architecture, investment case, and measurable outcomes.
Design scalable AI solutions using Gemini enterprise Agent Platform, Gemini models, Agent Development Kit (ADK), Agent Engine, Vertex AI Search, Vector Search, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP) integrations.
Architect cloud-native applications using Google Kubernetes Engine (GKE), Cloud Run, Cloud Functions, Pub/Sub, BigQuery, Cloud SQL, and Infrastructure as Code.
Design multi-agent architectures including orchestration, tool integration, memory management, observability, governance, and secure deployment patterns.
Lead architecture reviews and establish engineering standards for software quality, security, scalability, DevSecOps, CI/CD, testing strategies, and production readiness.
Guide clients through AI platform modernization initiatives while balancing innovation, security, governance, compliance, and operational excellence.
Collaborate with software engineers, platform engineers, data engineers, ML engineers, and client stakeholders to deliver enterprise AI solutions.
Work on delivery teams to build and deploy in a working, production-level AI solutions and software to client environments within the full software development lifecycle.
Establish clear technical direction and provide hands-on leadership through architecture reviews, design reviews, code reviews, engineering standards, troubleshooting, and production-readiness assessments.
Implement AI-enabled engineering practices within our project teams to help accelerate development.
Mentor technical teams and provide architectural guidance across multiple engagements while developing reusable engineering patterns and accelerators.
Build consensus across client, vendor, data, security, architecture, and engineering stakeholders when technical requirements or organizational priorities conflict.
Leverage AI tools to accelerate analysis, synthesize complex information, and support data-driven recommendations for clients, exercising sound judgment in evaluating outputs.
Apply AI technologies (e.g., generative AI, automation tools, data models) to enhance insights, improve delivery efficiency, and elevate the quality of client outcomes.
Serve as the Agentic AI Architect – Google Cloud and technical subject matter expert during pursuits, executive workshops, and client strategy engagements.
Develop AI platform roadmaps, solution architectures, technical estimates, and implementation strategies for enterprise clients.
Build trusted relationships with technology executives, engineering leaders, and Google Cloud stakeholders.
Identify opportunities to expand cloud modernization, AI platform engineering, intelligent application development, and software engineering engagements.
Support proposals, thought leadership, demonstrations, and technical solution development.
Establish and expand the Agentic AI Architect – Google Cloud capability by developing reusable assets, reference architectures, engineering standards, and delivery of accelerators for Google Cloud AI solutions.
Mentor consultants and engineers while promoting software engineering excellence and cloud-native architecture best practices.
Contribute to internal knowledge sharing, technical communities, white papers, and industry presentations focused on Google Cloud AI and agentic application development.
Stay current with emerging Google Cloud technologies, AI frameworks, and software engineering practices to continuously evolve West Monroe's AI Engineering capabilities.