Job Title : AI ML Ops Enterprise Architect
Location : Remote
Duration: 12 Months
Bill Rate: $66/hr. On W2
Client: To Be Discussed Later
Job type: W2-Contract
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Description:
- 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, Google Cloud Platform 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.
Equal Opportunity Employer: We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.
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