Senior AISolution Architect

CORE Occupational Medicine; Santa Ana (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

CORE Occupational Medicine seeks a Senior AI Solution Architect to lead data and AI platform architecture on Google Cloud Platform, based in Santa Ana, CA, for a 12-month contract. The role targets 10-15+ years of experience with 5+ years in AI/Data Architecture and hands-on work with modern data lakehouse, BI, ML/MLOps, GenAI, and agentic AI.

You will design end-to-end data and AI solutions, collaborate with data scientists and stakeholders, and drive enterprise-grade architecture using GCP

Qualifications

• 10-15+ years of overall experience in AI/data architecture roles.
• Strong hands-on experience with data lakehouse architectures and modern BI ecosystems.
• Deep expertise in AI/ML architecture, MLOps, and GenAI/Agentic AI frameworks.
• Proven ability to design enterprise-grade data and AI platforms on GCP.

Responsibilities

• Data & Platform Architecture: design end-to-end data architectures including ingestion, processing, storage, governance and consumption layers.
• Architect modern data lakehouse platforms using GCP services (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 for 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 implementGenAI solutions using LLMs; design conversational analytics and AI-powered BI.
• Build and evaluate agent-based systems, autonomous agents, and orchestration/tool integrations.
• Lead solution evaluations, PoCs, and vendor/tool assessments for GenAI and Agent-based systems.
• Business Intelligence & Analytics: design modern BI/analytics platforms for self-service insights; integrate BI with data layers.
• Cloud & Google Cloud Platform Leadership: lead architecture/design on GCP services, ensure security, scalability, and cost optimization.

Skills

Data Architecture

AI/ML Architecture

MLOps

Generative AI

Agentic AI

GCP Experience

Education

Bachelor's or Master's in CS/DS/Engineering

Tools

BigQuery

Vertex AI

Cloud Storage

Dataflow

Dataproc

Pub/Sub

Looker

TensorFlow

PyTorch

scikit-learn

Tableau/Power BI

Job description

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