Platform Architect - AI

Flex•Austin, TX

17h•Onsite

About The Position

Flex is seeking a Platform Architect to design and scale enterprise-grade platforms for deploying AI and data-driven applications across our global manufacturing and supply chain ecosystem. This role will focus on building secure, scalable, and developer-friendly platforms that accelerate the adoption of AI solutions—leveraging Google Cloud as a primary environment while enabling interoperability across Azure and AWS—and aligning with enterprise governance, compliance, and operational excellence standards. You will operate at the intersection of AI platform engineering, cloud architecture, and developer experience, enabling teams across engineering, data science, and business functions to rapidly build and deploy production-grade AI solutions. This role is based from our Austin, TX Corporate headquarters.

Requirements

5+ years of experience in platform engineering, cloud architecture, or related roles
Strong experience designing and deploying solutions on Google Cloud Platform
Experience building and scaling cloud-native platforms (APIs, microservices, data pipelines)
Hands-on experience with infrastructure-as-code (Terraform or similar) and CI/CD practices
Experience supporting production-grade data and analytics platforms
Proficiency in Python, Java, Go, or similar

Nice To Haves

Preferred Experience working in multi-cloud environments (GCP, Azure, AWS)
Experience with AI/ML platforms (Vertex AI, SageMaker, Azure ML, or similar)
Familiarity with modern data architectures (BigQuery, Snowflake, lakehouse, etc.)
Experience building internal developer platforms or self-service tooling
Exposure to enterprise security frameworks (IAM, zero trust, network segmentation)
Experience in manufacturing, supply chain, or industrial environments

Responsibilities

AI Platform Architecture & Deployment: Architect and evolve enterprise AI platforms supporting LLMs, AI agents, and advanced analytics workloads.
Design scalable deployment patterns for AI solutions (APIs, agents, pipelines) across cloud environments.
Enable self-service AI capabilities through reusable platform services and standardized deployment frameworks.
Cloud Architecture & Multi-Cloud Strategy: Lead architecture and implementation of AI and data platforms primarily on Google Cloud (Vertex AI, BigQuery, Cloud Run, Composer, etc.).
Define and implement multi-cloud design patterns spanning Google Cloud, Azure, and AWS, ensuring portability and flexibility.
Establish consistent infrastructure, networking, and governance models across cloud providers.
Developer Platform & Experience: Build and evolve internal developer platforms that simplify deployment of AI and data applications.
Develop CI/CD frameworks that support consistent deployment across multi-cloud environments.
Improve observability, reliability, and developer productivity through platform tooling and automation.
Data & AI Integration: Design architectures integrating AI systems with enterprise data sources (ERP, supply chain, manufacturing systems) across cloud environments.
Support real-time and batch data pipelines using cloud-native and cross-cloud data services.
Support scalable, governed data platforms leveraging modern architectures (lakehouse, medallion, etc.).
Security, Governance & Compliance: Implement secure-by-design architectures across Google Cloud, Azure, and AWS, including IAM, network controls, and data protection.
Establish guardrails for AI deployment, including access control, monitoring, and auditability.
Ensure compliance with global regulatory standards (GDPR, FDA, and other industry requirements).
Cross-Functional Collaboration: Partner with Data Science, R&D, IT, and business stakeholders to translate use cases into scalable platform capabilities.
Support lighthouse AI initiatives and drive broader enterprise adoption.
Mentor engineers and promote best practices in platform engineering and cloud architecture.