AI/ML Architect (Google Cloud Platform)

Overview

Hybrid
$75 - $85
Contract - W2
Contract - Independent

Skills

GCP
AI/ML
Generative AI
LLM
BigQuery

Job Details

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

Santa Ana - 4 Days Hybrid

Experience

10 15+ years overall experience (with 5+ 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 data lakehouse 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

  • Bachelor s or Master s 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

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.