Senior Data & AI Solutions Architect - Cloud Consulting

Google

Chicago (IL)

Hybrid

USD 152,000 - 221,000

Full time

40 hours ago

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Benefits offered by this job

Health, dental, vision, life,-disabil

401(k) with company match

Paid Time Off: 20 days per year

Sick Time: 40 hours/year (Seattle 69)

Maternity Leave: 28-30 weeks

Baby Bonding Leave: 18 weeks

Holidays: 13 paid days/year

Job summary

Google Cloud Professional Services is seeking a Technical Solutions Consultant to own the technical relationship with Google's largest advertising clients and product partners. You will lead cross-functional teams, supervise design-to-delivery cycles, and architect data-to-AI ecosystems using Vertex AI, BigQuery, Dataflow, and multi-agent technologies.

The role balances advisory work with hands-on delivery across on-site and remote locations in the US, shaping enterprise-scale architectures and

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.

Responsibilities

Architect enterprise-scale, production-ready Data-to-AI platforms, advanced 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 Gemini foundation model family.
Implement agentic reasoning loops, memory systems, tool and API integrations, and robust AgentOps frameworks for monitoring, tracing, evaluation, and cost control.
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 architectures.