Applied AI Senior SME​/Google Gemini Enterprise Architect San Ramon, California,

Job Title

Applied AI Senior SME / Google Gemini Enterprise Architect | Four Ways Consulting | San Ramon, California, USA

Four Ways Consulting

San Ramon, California, USA (Hybrid – 3 Days Onsite)

6+ Month Contract

• Hybrid Work Model (3 Days Onsite)
• Contract Duration: 6+ Months
• Senior-Level AI Leadership Role
• 7+ Years of Software Engineering Experience Required
• 2+ Years of Applied AI Experience Required
• Experience with Google Gemini Enterprise is Essential

Four Ways Consulting is seeking a highly experienced Applied AI Senior SME / Google Gemini Enterprise Architect to lead the design, governance, and deployment of enterprise-scale AI solutions leveraging Google Gemini and Vertex AI. This role is ideal for a hands‑on AI architect who combines deep technical expertise with strategic leadership to deliver secure, scalable, and production‑ready Generative AI applications.

As an Applied AI Senior SME, you will play a key role in shaping enterprise AI strategy and implementing next‑generation AI solutions built on Google Gemini Enterprise. Working closely with engineering, cloud, security, and business teams, you will design advanced AI architectures incorporating Multi‑Agent systems, Retrieval‑Augmented Generation (RAG), and enterprise knowledge platforms. You will be responsible for ensuring AI governance, security, observability, compliance, and operational excellence across the AI lifecycle.

The role requires strong experience in software engineering, AI architecture, cloud‑native deployments, and enterprise‑scale AI adoption. This opportunity offers exposure to cutting‑edge Generative AI technologies and large‑scale digital transformation initiatives.

• Architect and deploy enterprise AI solutions using Google Gemini Enterprise and Vertex AI.
• Design and implement Retrieval‑Augmented Generation (RAG) frameworks and knowledge retrieval systems.
• Build and orchestrate Multi‑Agent AI environments for complex business workflows.
• Develop enterprise AI applications using Google Agent Development Kit (ADK).
• Implement Model Context Protocol (MCP)-based integrations and AI workflows.
• Establish AI governance, security, compliance, and responsible AI frameworks.
• Design observability and monitoring solutions for AI models, agents, and enterprise AI platforms.
• Collaborate with software engineering teams to integrate AI capabilities into enterprise applications.
• Optimize AI performance, scalability, reliability, and operational efficiency.
• Lead architectural reviews, technical workshops, and AI transformation programs.
• Provide mentorship and technical leadership to engineering and AI teams.
• Develop best practices for enterprise AI deployment, security, and lifecycle management.

• Bachelor’s or Master’s Degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science, or a related field.
• Minimum 7 years of software engineering experience.
• Minimum 2 years of Applied AI or Generative AI implementation experience.
• Proven expertise with Google Gemini Enterprise.
• Hands‑on experience with Google Agent Development Kit (ADK).
• Strong understanding of Model Context Protocol (MCP).
• Experience designing and deploying Retrieval‑Augmented Generation (RAG) solutions.
• Strong proficiency in Python and/or Go.
• Experience with Google Cloud Platform (GCP) and Vertex AI.
• Strong understanding of Multi‑Agent AI architectures and orchestration.
• Experience implementing AI governance, security, compliance, and responsible AI practices.
• Knowledge of AI observability, monitoring, and operational management.
• Experience designing cloud‑native, highly scalable enterprise architectures.
• Strong communication, stakeholder management, and leadership skills.

• Experience with vector databases and semantic search platforms.
• Knowledge of Lang Chain, Lang Graph, CrewAI, Auto Gen, or similar agent frameworks.
• Hands‑on experience with Kubernetes, Docker, and containerized deployments.
• Familiarity with MLOps, CI/CD, and AI lifecycle management.
• Google Cloud Professional certifications or AI‑related certifications.

For AI Architect and SME‑level positions, employers prioritize candidates who have successfully moved AI initiatives from proof‑of‑concept to enterprise production. Highlight specific Gemini, Vertex AI, RAG, or Multi‑Agent implementations, emphasizing measurable business outcomes, governance frameworks, security controls, scalability achievements, and the real‑world impact your AI solutions delivered.