AI ML Ops Enterprise Architect

Skills: Digital: DevOps~Digital: Azure Machine Learning (ML)~Apache Beam~Enterprise Architecture. Mentor and guide technical teams on ML Ops architecture, tooling, and best.

Requisition ID: 104155 -1
Title: AI ML Ops Enterprise Architect
Duration: 12 months with possible extension
Location: Woodland Hills, CA or Remote
Salary Range: $50 -$55 an hour on W2/C2C

Job 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."

"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, GCP 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: 8-10


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