Senior AISolution Architect

Job Title: Senior AI Solution Architect - Data & AI Platforms (Google Cloud Platform)

Location: Santa Ana, CA

Duration : 12 months contract

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