AI Solution Architect

Job Description – Senior AI Solution Architect – Data & AI Platforms (GCP)

Job Title: Senior AI Solution Architect – Data & AI Platforms (GCP)

Location: Santa Ana, CA (Onsite)

Experience: 12-15+ years of experience (5+ years in AI/Data Architecture)

Job Summary

We are seeking an experienced Senior AI Solution Architect with expertise in Data Architecture, AI/ML, Generative AI, and Google Cloud Platform (GCP) to design and implement scalable, secure, enterprise-grade AI and data solutions. The ideal candidate will have strong hands-on experience with modern data platforms, MLOps, Data Lakehouse architectures, Conversational AI, Agentic AI frameworks, and Business Intelligence solutions.

Key Responsibilities Data & Platform Architecture

• Design end-to-end enterprise data architectures for ingestion, processing, storage, governance, and analytics.

• Architect scalable Data Lakehouse solutions using GCP services such as BigQuery, Cloud Storage, Dataproc, and Dataflow.

• Build batch, streaming, and real-time analytics platforms.

• Implement data governance, metadata management, lineage, data quality, and security frameworks.

AI/ML & MLOps

• Design enterprise AI/ML platforms supporting model development, deployment, monitoring, and lifecycle management.

• Implement MLOps best practices including CI/CD pipelines, Feature Stores, Model Registries, and model observability.

• Collaborate with Data Scientists to deploy production-ready ML models.

• Evaluate AI/ML frameworks, tools, and enterprise best practices.

Generative AI & Agentic AI

• Design and implement Generative AI solutions using Large Language Models (LLMs), embeddings, RAG, and multimodal AI.

• Build Conversational AI and AI-powered analytics solutions.

• Architect Agentic AI platforms using autonomous agents, orchestration frameworks, and tool integrations.

• Lead AI solution evaluations, Proof of Concepts (PoCs), and vendor assessments.

Business Intelligence & Analytics

• Design modern BI platforms supporting self-service analytics and AI-driven insights.

• Integrate BI tools with enterprise data platforms and AI ecosystems.

• Develop semantic layers, governed metrics, and enterprise reporting solutions.

Google Cloud Platform (GCP)

• Lead architecture and solution design on Google Cloud Platform.

• Utilize BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Looker, and IAM.

• Ensure solutions follow enterprise standards for scalability, security, performance, and cost optimization.

Leadership & Stakeholder Management

• Partner with business stakeholders to translate requirements into AI-powered solutions.

• Lead architecture reviews and technical governance.

• Mentor architects, engineers, and data scientists.

• Prepare architecture blueprints, technical documentation, and reference architectures.

Required Skills

• 10–15+ years of overall IT experience with 5+ years in AI/Data Architecture.

• Strong expertise in Data Architecture and Data Lakehouse platforms.

• Hands-on experience with Google Cloud Platform (BigQuery, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker, IAM).

• Experience designing enterprise AI/ML architectures and MLOps solutions.

• Strong knowledge of Generative AI, LLMs, Conversational AI, RAG, embeddings, and Agentic AI frameworks.

• Experience with Python, SQL, Spark, Kafka, and modern data engineering technologies.

• Expertise in Business Intelligence platforms such as Looker, Tableau, or Power BI.

• Strong understanding of cloud security, governance, scalability, and enterprise architecture principles.

• Excellent communication, leadership, and stakeholder management skills.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.

• Google Cloud Professional certifications (Professional Data Engineer, Professional ML Engineer, or Professional Cloud Architect).

• Experience working in large enterprise or consulting environments.

• Hands-on experience with TensorFlow, PyTorch, Scikit-learn, CI/CD pipelines, Feature Stores, and Model Registries.

• Experience leading enterprise AI transformation initiatives.