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Gemini Architect
Job Description:
- Architect end-to-end, scalable, secure, and performant GenAI solutions using Gemini Enterprise. Design complex, multi-agent workflows, deciding between the no-code workbench and custom Agent Development Kit (ADK) systems for production tasks.
- Design the RAG-based data grounding architecture to securely connect Gemini Enterprise models to diverse, permission-aware enterprise data (e.g., BigQuery, Salesforce).
- Architect the security and governance framework, implementing data residency, access control, and agent monitoring via Gemini Enterprise's control planes.
- Serve as the lead technical advisor to C-level and IT leadership, defining the strategic value, ROI, and technical roadmap for Gemini Enterprise adoption.
- Facilitate client workshops (requirements, validation, UAT). Lead hands-on development of high-impact prototypes/MVPs to validate architecture and demonstrate business value.
- Create the technical integration strategy to embed Gemini across the client's technology stack (Google Workspace, core business applications).
- Produce high-quality architectural documents, design specs, and roadmaps for implementation teams.
- Stay current with industry trends and advanced AI/ML, including agentic frameworks.
- Act as a key resource and contributor, lending your expertise to adjacent projects, special initiatives, and strategic conversations that align with your core competencies.
- Collaborate with delivery, engineering, and sales to define scope, identify opportunities, and evolve the Gemini Enterprise offering.
Requirements:
- 6+ years of experience in Solutions Architecture, Cloud Architecture, or Senior Technical Consulting, with a proven focus on AI/ML or complex, large-scale enterprise platforms.
- Deep, hands-on architectural expertise with the Gemini / Gemini Enterprise. This must include designing gems, agentic workflows, implementing data grounding strategies, and configuring security/governance controls.
- Demonstrable ability to analyze complex business problems, think strategically, and translate high-level objectives into robust, scalable, and secure technical architectures.
- Strong architectural understanding of the Google Workspace environment (Admin, Security, APIs) as a key integration point and data source for GenAI.
- Expertise in Large Language Models (LLMs), RAG techniques, prompt engineering, and API-first integration patterns.
- Proficiency with cloud architecture (preferably Google Cloud), data platforms (e.g., BigQuery), and at least one relevant scripting language (e.g., Python).
- Exceptional communication and presentation skills, with the ability to articulate complex architectural concepts to diverse audiences, from executive stakeholders to technical engineers.
- Proven experience leading technical delivery and managing client expectations in a consulting environment.
- Strong analytical and problem-solving skills, with a track record of innovation and technical leadership.
- Bachelor's degree in Computer Science, Engineering, or a related technical/quantitative field.
- Google Cloud Professional Certifications (e.g., Professional Cloud Architect, Machine Learning Engineer, or Professional Collaboration Engineer).
Benefits:
- Health insurance
- Professional development opportunities