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

Key Skills

Education

Any Gradute