Salary
💰 $143,360 - $255,500 per year
Tech Stack
AirflowAmazon RedshiftApacheAWSBigQueryCloudDistributed SystemsGoogle Cloud PlatformGuidewireKubernetes
About the role
- 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.
- Interprets internal/external business challenges and recommends best practices to improve products, processes or services.
- 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.
- 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.
- Lead Enterprise architecture delivery and influence strategy, roadmap, and data-driven insights across the organization.
Requirements
- 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).
- 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.
- 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.
- Bachelor's degree required.
- TOGAF Certified EA Architect preferred.
- Familiarity with Guidewire integrations is highly desirable.