Senior AI Solution Architect – Data & AI Platforms; Google Cloud Platform

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

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

Location:

Santa Ana, CA

CTH

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., Big Query, 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 product ionize 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 Big Query, 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:
  Big Query, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker
• AI/ML:
  Tensor Flow, 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

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