Data AI Solution Architect - #2092608

Role Overview

As a Data / AI Solution Architect, you will be responsible for defining scalable, secure, and resilient architectures for enterprise AI and data platforms. You will play a key role in shaping AI strategy, designing cloud-native solutions, enabling large-scale data modernization, and driving the adoption of emerging technologies including Generative AI, Agentic AI, RAG architectures, and LLMOps.

The role requires close collaboration with engineering teams, data scientists, platform teams, and business stakeholders to translate business requirements into enterprise-grade technical solutions.

Key Responsibilities

AI & Data Architecture

• Design end-to-end architectures for AI, Machine Learning, Generative AI, and enterprise data platforms.
• Define scalable and resilient cloud-native architectures aligned with business and platform objectives.
• Architect solutions supporting:
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Agentic AI workflows
• LLMOps and MLOps
• Data Analytics and Reporting Platforms
• Create reusable architecture patterns and standards for AI-enabled applications.

Cloud & Platform Architecture

• Design and implement solutions leveraging Google Cloud Platform services including:
• BigQuery
• Cloud Run
• Google Kubernetes Engine (GKE)
• Cloud Storage
• Dataflow
• Pub/Sub
• Vertex AI
• Looker
• Cloud Composer
• Drive cloud migration and modernization initiatives.
• Define cloud-native integration and deployment strategies.

Integration & Microservices

• Design API-first and event-driven architectures.
• Implement integration patterns using:
• Apigee
• Istio
• Service Mesh
• Kubernetes
• Event Streaming
• Design secure authentication and authorization mechanisms using:
• OIDC
• IAM
• Workload Identity
• API Security Policies

AI & Advanced Analytics

• Lead architecture decisions for:
• Generative AI
• LLM-based Applications
• Agentic Systems
• Workflow Automation
• AI Orchestration Frameworks
• Evaluate and implement AI governance, monitoring, and model lifecycle management practices.
• Support adoption of modern AI frameworks and tooling.

Governance & Security

• Ensure all solutions comply with enterprise architecture standards.
• Define secure-by-design architectures.
• Drive compliance with regulatory, security, risk, and data governance requirements.
• Participate in architecture review boards and governance forums.

Technical Leadership

• Lead architecture discussions and design workshops.
• Influence strategic technology direction across the platform.
• Provide mentorship and technical guidance to engineering and delivery teams.
• Communicate complex technical concepts to both technical and non-technical stakeholders.

Required Skills & Experience

Cloud Architecture

• Extensive experience designing solutions on:
• Google Cloud Platform (GCP)
• Microsoft Azure (desirable)
• Strong knowledge of cloud-native architecture patterns.
• Experience designing highly available and scalable enterprise platforms.

Data & AI Architecture

• Strong experience with:
• Data Architecture
• Machine Learning
• Artificial Intelligence
• Data Engineering
• Modern Data Platforms
• Knowledge of:
• LLMs
• RAG Architectures
• Agentic AI
• LLMOps / MLOps
• AI Governance

Google Cloud Technologies

• BigQuery
• Cloud Run
• GKE (Google Kubernetes Engine)
• Dataflow
• Pub/Sub
• Cloud Composer
• Cloud Storage
• Vertex AI
• Looker