ML Ops Architect (Lead Enterprise Architect)

Job Summary

Designs and develops IT architecture strategy, standards and roadmap while creating Enterprise architecture delivery (integrated process, applications, data and technology) in alignment with Enterprise architecture vision and direction. Requires specialized depth and/or breadth of expertise in Enterprise Architecture or related field. Interprets internal/external business challenges and recommends best practices to improve products, processes or services.

(Internal position title: Lead Enterprise Architect)

What You'll Do

• 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.

What You'll Bring

• 6 years relevant experience in Enterprise Architecture 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

Education Requirements

• Bachelor's degree required.
• TOGAF Certified EA Architect preferred.

Physical Actions

Sits or stands for extended periods of time, up to a full work shift. Occasionally reaches overhead and below the knees, including bending, twisting, pulling, and stooping. Occasionally moves, lifts, carries, and places objects and supplies weighing 0-10 pounds without assistance. Listens to, interprets, and differentiates auditory information (e.g. others speaking) at normal speaking levels with or without correction. Visually verifies and reads information. Visually locates material, resources and other objects. Ability to operate a computer for extended periods of time, up to a full work shift. Physical dexterity sufficient to use hands, arms, and shoulders repetitively to operate keyboard and other office equipment up to a full work shift.

Physical Environment

This position operates in an open office working environment which will include normal and customary distractions, noise, and interruptions.