Senior AI Solution Architect (Google Cloud Platform)

Overview

On Site
/
Contract - W2
Contract - CON_HIRE_W2

Skills

Big Query
Vertex AI
Cloud Storage
Dataflow
Dataproc
Pub/Sub
Looker
Data Architecture
AI/ML platforms
and Generative AI solutions
datalake house architectures
modern BI platforms
ML/MLOps
Conversational Analytics
Generative AI
and Agentic AI frameworks

Job Details

Senior AI Solution Architect Data & AI Platforms (Google Cloud Platform)

Location: Santa Ana, CA


Experience

1015%2B years overall experience (with 5%2B years in AI/Data Architecture roles)

Job Summary

We are seeking a highly skilled AI Solution Architect with deep expertise in Data Architecture, AI/ML platforms, and Generative AI solutions, to design and deliver scalable, secure, and enterprise-grade data and AI solutions on Google Cloud Platform (Google Cloud Platform).

The ideal candidate will have strong hands-on experience across datalake house architectures, modern BI platforms, ML/MLOps, Conversational Analytics, Generative AI, and Agentic AI frameworks, and will work closely with business, data engineering, and AI teams to drive end-to-end AI-led transformation.

Key Responsibilities

Data & Platform Architecture

  • Design and own end-to-end data architectures including ingestion, processing, storage, governance, and consumption layers
  • Architect modern data lakehouse platforms using Google Cloud Platform services (e.g., BigQuery, Dataproc, Cloud Storage)
  • Define scalable data platforms supporting batch, streaming, and real-time analytics
  • Establish data governance, metadata management, data quality, lineage, and security frameworks

AI, ML & MLOps Architecture

  • Design ML/AI architectures supporting model training, deployment, monitoring, and lifecycle management
  • Define and implement MLOps frameworks (CI/CD for ML, feature stores, model registries, observability)
  • Collaborate with data scientists to productionize ML models at scale
  • Evaluate and recommend ML frameworks, tools, and best practices

Generative AI & Agentic AI

  • Architect and implement Generative AI solutions using LLMs (e.g., text, code, embeddings, multimodal use cases)
  • Design Conversational Analytics and AI-powered BI solutions
  • Build and evaluate Agentic AI platforms, including autonomous agents, orchestration frameworks, and tool integrations
  • Lead solution evaluations, PoCs, and vendor/tool assessments for GenAI and Agent-based systems

Business Intelligence & Analytics

  • Design modern BI and analytics platforms enabling self-service analytics and AI-driven insights
  • Integrate BI tools with data lakehouse and AI layers
  • Enable semantic layers, metrics definitions, and governed analytics

Cloud & Google Cloud Platform Leadership

  • Lead architecture and solution design on Google Cloud Platform (Google Cloud Platform)
  • Utilize Google Cloud Platform services such as BigQuery, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker, and IAM
  • Ensure architectures follow best practices for security, scalability, performance, and cost optimization

Stakeholder & Technical Leadership

  • Partner with business leaders to translate business requirements into AI-driven solutions
  • Lead technical design reviews and architecture governance
  • Mentor engineers, architects, and data scientists
  • Create architecture blueprints, reference architectures, and technical documentation


Required Skills & Qualifications

Core Technical Skills

  • Strong experience in Data Architecture & Data Platforms
  • Hands-on expertise in Data Lakehouse architectures
  • Deep understanding of end-to-end data management
  • Experience with modern BI platforms and analytics ecosystems
  • Strong background in AI/ML architecture and MLOps
  • Proven experience in Conversational Analytics and Generative AI
  • Hands-on exposure to Agentic AI platforms, frameworks, and evaluations
  • Strong expertise in Google Cloud Platform (Google Cloud Platform)


Tools & Technologies (preferred)

  • Google Cloud Platform: BigQuery, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker
  • AI/ML: TensorFlow, PyTorch, scikit-learn, LLM frameworks
  • MLOps: CI/CD, feature stores, model registries, monitoring tools
  • Data: SQL, Python, Spark, Kafka
  • BI: Looker, Tableau, Power BI (or equivalent)


Preferred Qualifications

  • Bachelors or Masters degree in Computer Science, Data Science, Engineering, or related field
  • Google Cloud Platform Professional certifications (e.g., Professional Data Engineer, Professional ML Engineer, Cloud Architect)
  • Experience working in large-scale enterprise or consulting environments
  • Strong communication and stakeholder management skills



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