Job ID: JOB_ID_2970
Job Overview:
We are seeking a highly skilled and experienced MLOps Lead Architect to design, implement, and manage scalable AWS ML/AI cloud infrastructure within a multi-tenant SaaS environment. This role involves close collaboration with data scientists, data engineers, and IT teams to establish best practices for ML model development, deployment, and monitoring. You will be instrumental in evaluating and recommending cutting-edge tools and platforms, ensuring alignment with enterprise architecture standards, and overseeing the integration of ML pipelines with existing enterprise systems. Familiarity with Guidewire integrations is a significant plus.
Key Responsibilities:
- 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.
Required Experience:
Data & Analytics Technology Experience:
- 5+ years: AI/ML Strategy & Roadmap Development.
- 4+ years: MLOps Tools (e.g., AWS Sagemaker, GCP Vertex AI, Databricks).
- 3+ years: ML & Data Pipeline Orchestration (e.g., Kubeflow, Apache Airflow).
- 2+ years: ML Feature Store Tools (e.g., Tecton, Databricks, FeatureForm).
- 3+ years: DevOps (e.g., Argo CD / Argo Workflows), Containerization (Kubernetes, ROSA).
- 3+ years: Enterprise Application Integration (e.g., Guidewire, Salesforce).
- 4+ years: Data Platforms (e.g., Snowflake, RedShift, BigQuery).
- 2+ years: GenAI Tools / LLMs (e.g., OpenAI, Gemini, etc.).
- 1+ year: Agentic AI Frameworks (e.g., LangGraph, Autogen, Google ADK).
- 3+ years: API Orchestration (e.g., Mulesoft, Google Cloud API).
Architecture Experience:
- 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:
- 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: Machine Learning
- Keywords: continuous deployment, artificial intelligence, machine learning, information technology, California
Overall Experience:
- 10+ years
Special Requirements
Interview Mode: In-person (implied by location). Domain Restrictions: Insurance domain knowledge preferred.
Compensation & Location
Salary: $150,000 – $190,000 per year (Estimated)
Location: Woodland Hills, CA
Recruiter / Company – Contact Information
Recruiter / Employer: Sira Consulting
Email: manish@siraconsultinginc.com
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