Principal Forward Deployed Architect, GCP

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Forward Deployed Architect, GCP based in the United States.

This is a senior technical leadership role focused on turning ambitious enterprise GenAI strategies into durable business outcomes. You will own the end-to-end architecture of production agent ecosystems built on Google Cloud and Gemini Enterprise technologies. The role spans the GenAI platform foundation, agent landscape, context-graph and data foundation, governance, and enterprise adoption. You will serve as the senior technical counterpart to executive stakeholders, guiding architecture decisions, sequencing delivery, and managing technical risk. The position combines deep hands-on architecture with client advisory, commercial support, and technical team leadership. It is ideal for an experienced cloud and AI architect who can connect complex technical systems to measurable business value.

Accountabilities:

You will own technical coherence and business outcomes across major Gemini Enterprise engagements, guiding architecture, delivery, client relationships, and technical practice development.

• Own the target architecture across the GCP GenAI platform foundation, GEAP agent landscape, context-graph and data foundation, and enterprise adoption layers.
• Define reference patterns for agent development, deployment, isolation, runtime environments, and governance.
• Design context-graph foundations using technologies such as BigQuery, BigQuery Graph (GQL), and Spanner Graph.
• Develop grounding and RAG strategies connecting enterprise data and knowledge foundations to AI agents, including entity resolution, semantic modeling, and retrieval through Vertex AI Vector Search.
• Identify dependencies and cross-layer architectural decisions that could affect runtime, data residency, security, governance, or delivery sequencing.
• Arbitrate technical trade-offs across multiple engineering workstreams and document architectural decisions and their rationale.
• Review agent designs, evaluation results, trajectory and latency behavior, and participate in incident reviews and selective hands-on technical work.
• Represent the technical program in client security, compliance, architecture, model-governance, and data-governance forums.
• Advise executive stakeholders on technical trade-offs, delivery sequencing, risks, automation readiness, and use cases that may not yet be appropriate for automation.
• Own technical scope, estimates, and technical defense of proposals and statements of work for major opportunities.
• Provide leadership with visibility into delivery risks, remediation plans, and cloud consumption-cost exposure.
• Enable client platform, data, and security teams to operate and extend the agent ecosystem and context graph independently.
• Develop and mentor Forward Deployed Engineers working across client engagements.
• Contribute reference architectures, context-graph patterns, estimation models, and governance blueprints to strengthen technical practices.
• Remain accountable for long-term outcomes, ensuring deployed agent ecosystems remain grounded, governed, evaluated, adopted, and aligned with their intended business objectives.

Requirements:

The ideal candidate is a highly experienced technology leader with deep expertise in cloud architecture, GenAI or agent platforms, enterprise data foundations, and production systems. You should be comfortable owning complex client engagements from discovery through production while advising executives and leading multidisciplinary technical teams.

• Master’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
• 12+ years of experience in engineering, architecture, or technical delivery leadership, including senior ownership of production systems.
• Expert-level depth in at least two of the following areas: agent/GenAI platforms, context graphs and semantic modeling, cloud data platforms, or cloud runtime and governance.
• Working competence across the remaining architecture layers, demonstrated through an architecture walkthrough.
• Experience delivering at least one production GenAI or agent system on GCP, Vertex AI, Agent Platform, or a directly comparable cloud environment.
• Experience implementing grounding over an enterprise data or knowledge foundation.
• End-to-end ownership of technical design for at least two client engagements or major cross-team programs, from discovery through production.
• Experience serving as the senior technical counterpart to executive stakeholders on significant client engagements.
• Hands-on expertise with BigQuery and at least one graph or semantic data store, such as Spanner Graph, BigQuery Graph, Neo4j, or an equivalent technology.
• Experience delivering solutions in at least one regulated environment and the ability to explain how regulatory requirements influenced architectural decisions.
• Experience owning technical scope, estimates, and technical defense of proposals or statements of work.
• Strong client advisory, communication, architecture, problem-solving, and technical leadership skills.
• Hands-on experience with the Gemini Enterprise Agent Platform, including ADK, Agent Garden, Model Garden, or Agent Engine, is preferred.
• Demonstrated ability to rapidly build expertise in adjacent agent frameworks and technologies is a plus.

Benefits:

• Full-time remote position based in the United States.
• Opportunity to lead large-scale enterprise GenAI and agent architecture initiatives.
• Work with Google Cloud, Gemini Enterprise technologies, and modern AI infrastructure.
• High level of technical ownership across architecture, delivery, governance, and adoption.
• Direct exposure to executive stakeholders and complex enterprise transformation programs.
• Opportunity to mentor experienced engineers and influence technical standards and reference architectures.
• Ability to contribute to emerging GenAI architecture patterns, governance frameworks, and delivery methodologies.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.