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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI ML Ops Enterprise Architect - **Company:** Purple Drive Technologies LLC - **Location:** Culver City, CA, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Applications Architecture, BigQuery, Software as a Service, Cloud Computing, Data Architecture, DevOps, Distributed Systems, Machine Learning, Octopus Deploy, Salesforce.Com, Enterprise Application Integration, Google Cloud, Large Language Models, Snowflake, Generative AI, Event Driven Architecture, Containerization, Kubernetes, Data Analytics, Data Management, Machine Learning Operations, Virtual Agents, Artificial Intelligence Markup Language (AIML), Data Pipelines, Guidewire, Mulesoft, Amazon Redshift, Databricks - **Published:** August 12, 2026 - **Apply:** https://www.dice.com/job-detail/ed8a23be-f74b-4e77-92fa-41c99efe96d6 ## About the Role * Minimum ten years experience across architecture disciplines with significant enterprise architecture leadership experience required. Data & Analytics Technology Experience Required * 5+ years: AI/ML Strategy & Roadmap Development. * 4+ years: MLOps Tools (Eg. AWS Sagemaker, Google Cloud Platform Vertex AI, Databricks). * 3+ years: ML & Data Pipeline Orchestration (Eg. Kubeflow, Apache Airflow). * 2+ years: ML Feature Store Tools (Eg. Tecton, Databricks, FeatureForm). * 3+ years: DevOps (Eg. Argo CD / Argo Workflows), Containerization (Kubernetes,ROSA). * 3+ years: Enterprise Application Integration (Eg. Guidewire, Salesforce). * 4+ years: Data Platforms (Eg. Snowflake, RedShift, BigQuery). * 2+ years: GenAI Tools / LLMs (Eg. OpenAI, Gemini, etc.). * 1+ year: Agentic AI Frameworks (Eg. LangGraph, Autogen, Google ADK). * 3+ years: API Orchestration (Eg. Mulesoft, Google Cloud API). Architecture Experience Required * 3+ years: Data Mesh Architecture & Data Product Design. * 3+ years: Event-Driven Architecture (EDA). * 4+ years: Scalable AWS ML/AI Cloud Infrastructure (Multi-tenant SaaS). * 3+ years: Data Architecture Guidelines Development. * 3+ years: Security in Distributed Systems. * 4+ years: Designing Scalable, Decoupled Systems. * 5+ years: Strategy & Roadmap Creation. * 3+ years: Influencing with Data-Driven Insights. Domain Experience Required * 4+ years: Functional Knowledge of Insurance Domains (Policy, Claims, Services Ops) - Preferred. * 2+ years: Legal & Compliance Regulations in Insurance - Preferred. * 3+ years: Data Product Development for Functional Domains. * 2+ years: AI-Driven Business Process Automation." CONTRACTOR, FULL_TIME, PART_TIME ## Description * Architect and implement scalable AWS ML/AI cloud infrastructure in a multi-tenant SaaS environment. * Collaborate with data scientists, data engineers, and IT teams to define requirements and best practices for ML model development, deployment, and monitoring. * Evaluate and recommend tools, platforms, and cloud technologies for ML Ops, ensuring alignment with enterprise architecture standards. * Oversee the integration of ML pipelines with existing enterprise data and application architectures. Familiarity with Guidewire integrations is highly desirable. * Oversee ML/AI related Kubernetes cluster management and provide guidance on alternative ML/AI workflow orchestration options such as Argo vs Kubeflow, and ML/AI data pipeline creation, management and governance with tools like Airflow. * Employ tools like Argo CD to automate infrastructure deployment and management. * Mentor and guide technical teams on ML Ops architecture, tooling, and best practices ## Related Videos - [Why make use of an integration platform in today's software developments and infrastructure?](https://www.wearedevelopers.com/videos/758-why-make-use-of-an-integration-platform-in-today-s-software-developments-and-infrastructure) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)