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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Ops Enterprise Architect - **Company:** PROLIM Global Corporation - **Location:** Los Angeles, CA, United States (Remote available) - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Applications Architecture, BigQuery, Software as a Service, Cloud Computing, Data Architecture, DevOps, Distributed Systems, Machine Learning, Octopus Deploy, OpenAI, Data Mesh, Azure Machine Learning, Salesforce.Com, Software Deployment, Systems Integration, AI Infrastructure, Enterprise Data Management, Enterprise Application Integration, Feature Store, Google Cloud, Enterprise Software Applications, Large Language Models, Snowflake, Google Vertex AI, Agentic-AI, Event Driven Architecture, AI Platforms, Kubernetes, AutoGen, Data Management, Machine Learning Operations, Google Gemini, Data Pipelines, Apache Beam, Guidewire, Mulesoft, Amazon Redshift, Databricks - **Published:** October 29, 2026 - **Apply:** https://www.careerbuilder.com/job-details/ai-ml-ops-enterprise-architect-los-angeles-ca--4ff7e049-b646-485a-a807-0cfda931e4ee ## About the Role Enterprise Architecture, Artificial Intelligence (AI), Artificial Intelligence (AI), Enterprise Architecture, Cloud Computing, Amazon Web Services (AWS), Enterprise Data Integration, Software as a Service (SaaS), Data Science, Best Practices, We are seeking a Senior AI/ML Ops Enterprise Architect with 10+ years of enterprise architecture experience and strong expertise in AWS cloud, MLOps, AI/ML infrastructure, Kubernetes, data architecture, and enterprise integrations., * 10+ years of experience across architecture disciplines with significant enterprise architecture leadership. * 5+ years developing AI/ML strategy and technology roadmaps. * 4+ years of MLOps experience with platforms such as AWS SageMaker, GCP Vertex AI, or Databricks. * 3+ years with ML/data pipeline orchestration technologies such as Kubeflow and Apache Airflow. * 2+ years with ML feature store technologies such as Tecton, Databricks, or FeatureForm. * 3+ years with DevOps, Kubernetes/containerization, and technologies such as Argo CD or Argo Workflows. * 3+ years of enterprise application integration experience; Guidewire or Salesforce is highly desirable. * 4+ years with data platforms such as Snowflake, Amazon Redshift, or BigQuery. * 2+ years working with GenAI/LLM technologies such as OpenAI or Gemini. * 1+ year with Agentic AI frameworks such as LangGraph, AutoGen, or Google ADK. * 3+ years of API orchestration experience with MuleSoft or Google Cloud API technologies. * Strong experience with AWS, Azure ML, Kubernetes, Apache Beam, and enterprise architecture. Architecture Experience * 3+ years with Data Mesh Architecture and Data Product Design. * 3+ years with Event-Driven Architecture (EDA). * 4+ years designing scalable AWS ML/AI infrastructure in multi-tenant SaaS environments. * 3+ years developing data architecture guidelines and standards. * 3+ years of security experience in distributed systems. * 4+ years designing scalable, decoupled enterprise systems. * 5+ years of technology strategy and roadmap development. * Strong ability to influence architecture decisions using data-driven insights. Preferred Domain Experience * 4+ years of functional knowledge in Insurance, including Policy, Claims, and Services Operations. * 2+ years of experience with insurance legal, regulatory, and compliance requirements. * 3+ years of data product development for functional business domains. * 2+ years of experience delivering AI-driven business process automation. * Experience with Guidewire integrations is highly preferred. ## Description The ideal candidate will architect scalable ML/AI platforms in a multi-tenant SaaS environment, establish MLOps strategy and best practices, and work closely with data scientists, data engineers, DevOps, and enterprise IT teams., * Architect and implement scalable AWS ML/AI cloud infrastructure for multi-tenant SaaS environments. * Define enterprise standards and best practices for ML model development, deployment, monitoring, and governance. * Collaborate with data scientists, data engineers, and IT teams to establish MLOps requirements and architecture. * Evaluate and recommend MLOps platforms and technologies such as AWS SageMaker, Databricks, and Vertex AI. * Integrate ML pipelines with enterprise data and application architectures; Guidewire integration experience is highly desirable. * Provide architecture guidance for Kubernetes-based ML/AI environments. * Evaluate and guide workflow orchestration technologies such as Argo, Kubeflow, and Apache Airflow. * Design and govern ML/AI data pipelines, feature stores, and data products. * Use Argo CD / Argo Workflows for automated infrastructure and application deployment. * Establish security, governance, scalability, and reliability standards for distributed AI/ML systems. * Mentor technical teams on MLOps architecture, tooling, DevOps practices, and enterprise architecture standards.