Google Gemini AI Architect

Google Gemini AI Architect

Location: Cleveland, OH

Duration: Fulltime

Job Description:

Must Have Technical/Functional Skills:

• Experience: Requires 6+ years in solutions architecture, AI/ML engineering, or technical consulting. The experience should include at least 1–2+ years focused specifically on LLMs and Generative AI in production.

• Technical skills: Requires deep knowledge of Vertex AI, Python, BigQuery, and Google Kubernetes Engine (GKE), Vector databases

• Cloud proficiency: Requires strong experience with Google Cloud Platform (GCP) and infrastructure-as-code (Terraform).

• Certifications: Google Cloud Professional Certifications, such as Professional Cloud Architect or Machine Learning Engineer.

• Demonstratable experience on GCP

• Verbal and written communication skills

Roles & Responsibilities:

We are looking for a Google Gemini AI Architect with strong manufacturing domain expertise and consulting mindset to help industrial enterprises design, deploy, and scale data and AI platforms across plants and enterprise systems

Travel: 25–30% (plants, client workshops, exec reviews)

Responsibilities:

• AI architecture and design: Architecting end-to-end Generative AI solutions, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent systems, and prompt engineering strategies.

• Vertex AI and Gemini integration: Integrating Gemini Pro/Ultra models into enterprise applications, managing fine-tuning, evaluation, and inference optimization.

• Security and governance: Implementing AI guardrails, ensuring security, data privacy, and compliance within AI workflows (e.g., managing data residency and access controls).

• Strategic advisory: Acting as a technical advisor to C-level stakeholders, defining roadmaps, ROI, and best practices for adopting Google Gemini Enterprise.

• Prototyping and development: Leading hands-on development of Proofs of Concept (PoCs) and Minimum Viable Products (MVPs) to validate designs.

Innovation and Experimentation:

• Evaluate and prototype new tools and techniques in autonomous agents, synthetic data generation, multi-modal models, and AI orchestration.

• Collaborate with product and business teams to conceptualize AI-powered assistants, copilots, and automation flows.

Leadership and Mentorship:

• Provide technical leadership to data scientists, prompt engineers, and AI developers.

• Promote a culture of innovation, experimentation, and measurable business impact through AI.

Generic Managerial Skills, If any:

• Coordination and collaboration with multiple stakeholders

• Guiding and leading the team members

• Strong communication skills