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Neurealm

AI Solution Architect – Data & AI Platforms (GCP)

Neurealm, Santa Ana, California, United States, 92725

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AI Solution Architect – Data & AI Platforms (GCP) Location: Santa Ana

Experience: 10–15+ years overall experience (with 5+ years in AI/Data Architecture roles)

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 (GCP) .

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

Design and own

end-to-end data architectures

including ingestion, processing, storage, governance, and consumption layers

Define scalable

data platforms

supporting batch, streaming, and real-time analytics

Establish data governance, metadata management, data quality, lineage, and security frameworks

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

Lead architecture and solution design on

Google Cloud Platform (GCP)

Utilize GCP 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 (GCP)

Tools & Technologies (preferred)

GCP: BigQuery, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker

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

GCP 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

Seniority level Mid‑Senior level

Employment type Full‑time

Job function Information Technology

Industries IT Services and IT Consulting

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