Job description

As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms and/or product partnerships. You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources. As a Data and AI Consultant within the Google Cloud Professional Services Organization (PSO), you will be the cornerstone of customers' digital transformation, designing and building the data-to-AI ecosystems that power everything from enterprise-wide analytics to cutting-edge generative AI and autonomous agentic systems. You will lead technical delivery, serving as a trusted advisor who architects and builds scalable, secure, and future-proof full-stack data and AI solutions. Your role requires deep expertise in data architecture, software engineering, and modern generative AI frameworks, enabling customers to not only manage their data but to develop and deploy production-grade agentic workflows, multi-agent systems, and cognitive architectures. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . • Architect enterprise-scale, production-ready Data-to-AI platforms, advanced Retrieval-Augmented Generation (RAG) pipelines, semantic knowledge graphs, and vector databases using Vertex AI Vector Search to support scalable generative AI applications. • Lead end-to-end implementation of Google Cloud data platforms using BigQuery, Dataflow, Pub/Sub, and AlloyDB, building high-throughput batch and streaming pipelines that optimize complex query performance. • Design, build, and deploy autonomous AI agents and multi-agent coordination systems by leveraging the Vertex AI Agent Ecosystem, Reasoning Engine, and the comprehensive Gemini foundation model family. • Implement agentic reasoning loops, memory systems, tool and API integrations, and robust AgentOps frameworks for continuous monitoring, tracing, evaluation, fine-tuning, latency optimization, cost control, and safety compliance. • Advise executive stakeholders on generative AI transformation, lead technical scoping and rapid prototyping workshops, and mentor engineering teams in modern Google Cloud Data and AI system architectures. • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. • 5 years of customer-facing experience as a Solutions Architect, Solution Engineer, or Software Engineer within a professional services or consulting environment. • Experience in building and managing data platforms (warehouses, lakes, streaming pipelines) on Google Cloud or another cloud provider. • Experience with Generative AI development, including working with Large Language Models (LLMs), API integrations, and RAG architectures. • Experience building and deploying production-grade full-stack applications (Python/Node.js backend, React/Angular frontend) and cloud-native solutions. Minimum qualifications: • Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience. • 5 years of customer-facing experience as a Solutions Architect, Solution Engineer, or Software Engineer within a professional services or consulting environment. • Experience in building and managing data platforms (warehouses, lakes, streaming pipelines) on Google Cloud or another cloud provider. • Experience with Generative AI development, including working with Large Language Models (LLMs), API integrations, and RAG architectures. • Experience building and deploying production-grade full-stack applications (Python/Node.js backend, React/Angular frontend) and cloud-native solutions. Preferred qualifications: • Experience with CI/CD, IaC (Terraform), containers (Docker, GKE, Cloud Run), and agent evaluation/tracing. • Expertise designing autonomous multi-agent frameworks, cognitive workflows, and orchestrators (Vertex AI Agent Builder, Gemini Enterprise). • Proficient across Google Cloud data/AI services (Vertex AI, BigQuery, Dataflow, Spanner, Firestore, Vector Search). • Proven stakeholder management, advising C-level leaders, facilitating architecture workshops, and driving client enablement. • Track record leading delivery teams, architecting enterprise software, and executing cloud modernizations.

Requirements

Must-haves

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Lead end-to-end implementation of Google Cloud data platforms using BigQuery, Dataflow, Pub/Sub, and AlloyDB, building high-throughput batch and streaming pipelines that optimize complex query performance.
Design, build, and deploy autonomous AI agents and multi-agent coordination systems by leveraging the Vertex AI Agent Ecosystem, Reasoning Engine, and the comprehensive Gemini foundation model family.
Advise executive stakeholders on generative AI transformation, lead technical scoping and rapid prototyping workshops, and mentor engineering teams in modern Google Cloud Data and AI system architectures.
Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
5 years of customer-facing experience as a Solutions Architect, Solution Engineer, or Software Engineer within a professional services or consulting environment.
Experience in building and managing data platforms (warehouses, lakes, streaming pipelines) on Google Cloud or another cloud provider.
Experience with Generative AI development, including working with Large Language Models (LLMs), API integrations, and RAG architectures.
Experience building and deploying production-grade full-stack applications (Python/Node.js backend, React/Angular frontend) and cloud-native solutions.
Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
5 years of customer-facing experience as a Solutions Architect, Solution Engineer, or Software Engineer within a professional services or consulting environment.
Experience in building and managing data platforms (warehouses, lakes, streaming pipelines) on Google Cloud or another cloud provider.
Experience with Generative AI development, including working with Large Language Models (LLMs), API integrations, and RAG architectures.
Experience building and deploying production-grade full-stack applications (Python/Node.js backend, React/Angular frontend) and cloud-native solutions.

Nice-to-haves

US: $152000 - $221000 (USD) + 15% bonus target + equity + benefits
Experience with CI/CD, IaC (Terraform), containers (Docker, GKE, Cloud Run), and agent evaluation/tracing.
Expertise designing autonomous multi-agent frameworks, cognitive workflows, and orchestrators (Vertex AI Agent Builder, Gemini Enterprise).
Proficient across Google Cloud data/AI services (Vertex AI, BigQuery, Dataflow, Spanner, Firestore, Vector Search).
Proven stakeholder management, advising C-level leaders, facilitating architecture workshops, and driving client enablement.
Track record leading delivery teams, architecting enterprise software, and executing cloud modernizations.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiapipythonnode.jsreactangularci/cddocker

Platform: google
Effort: medium