AI ML Ops Enterprise Architect at ONSITE- Woodland Hills, CA or Remote

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Role: AI ML Ops Enterprise Architect

Descriptions:

"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."

"Experience Requirements
 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."

Skills: Digital : DevOps~Digital : Azure Machine Learning (ML)~Apache Beam~Enterprise Architecture
Experience Required: 13+