Google Gemini AI Architect

Centraprise Corp
Cleveland, United States of America
6 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior

Job location

Cleveland, United States of America

Tech stack

Artificial Intelligence
Google BigQuery
Cloud Computing
Python
Machine Learning
Performance Tuning
Systems Integration
Google Cloud Platform
Enterprise Software Applications
Large Language Models
Multi-Agent Systems
Prompt Engineering
IT Architecture
Generative AI
Kubernetes
Terraform
Automation Anywhere
Data Generation

Job description

  • 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.

Requirements

  • 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, Big Query, and Google Kubernetes Engine (GKE), Vector databases
  • Cloud proficiency: Requires strong experience with Google Cloud Platform (Google Cloud Platform) and infrastructure-as-code (Terraform).
  • Certifications: Google Cloud Professional Certifications, such as Professional Cloud Architect or Machine Learning Engineer.
  • Demonstratable experience on Google Cloud Platform
  • Verbal and written communication skills, * Coordination and collaboration with multiple stakeholders
  • Guiding and leading the team members
  • Strong communication skills

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