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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise Architect - **Company:** UST Inc - **Location:** Aliso Viejo, CA, United States (Remote available) - **Experience:** Expert - **Salary:** $106,000 - $159,000 - **Contract:** Temporary contract - **Skills:** LangGraph Framework, ASP.NET, Java (Programming Language), .NET Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, C Sharp (Programming Language), Cloud Engineering, Data Governance, Information Leak Prevention, Distributed Systems, Entity Framework, Fault Tolerance, Key Management, OAuth, Open Source Technology, OpenID, RabbitMQ, OpenAI, Zero Trust Network Access, Search Technologies, Software Engineering, Enterprise Search, Azure Service Bus, Pinecone, Google Cloud, LangChain, Retrieval-Augmented Generation, Open-source Models, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Model Validation, Generative AI, Agentic-AI, Event Driven Architecture, Pgvector, AI Platforms, Kubernetes, Weaviate, AutoGen, Apache Kafka, Data Management, Machine Learning Operations, Semantic Kernel, Api Management, Microservices - **Published:** November 5, 2026 - **Apply:** https://diversityjobs.com/career/18842215/Enterprise-Architect-California-Aliso-Viejo ## About the Role * 15 to 18 years of experience in software engineering and architecture, with at least 5 years in an enterprise architect or principal-level role. * Strong expertise in Java (Spring Boot, Jakarta EE, microservices) or .NET (C#, ASP.NET Core, Entity Framework). Experience with both is a plus. * Proven experience designing distributed, high-throughput, fault-tolerant systems using event-driven architecture, messaging (Kafka, RabbitMQ, Azure Service Bus), and API management. * Hands-on working knowledge of Generative AI, including LLM APIs (OpenAI, Azure OpenAI, Anthropic, Google, or open-source models), prompt engineering, embeddings, and RAG. * Working knowledge of Agentic AI frameworks and patterns (for example, LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent), including tool use, planning, and agent evaluation. * Experience with vector databases (Azure AI Search, Pinecone, Weaviate, pgvector, or similar) and data platforms supporting AI workloads. * Solid cloud architecture experience on at least one major provider, with containers, Kubernetes, and infrastructure-as-code. * Strong understanding of enterprise security (OAuth2, OIDC, zero trust, secrets management) and AI-specific risks such as prompt injection, data leakage, and model misuse. * Excellent written and verbal communication skills, with the ability to present to CxO and steering committee audiences. Preferred * Experience in regulated industries such as banking, insurance, healthcare, or telecom. * Familiarity with MLOps/LLMOps practices, model monitoring, and evaluation tooling. * Contributions to open-source projects, published articles, or speaking engagements on AI or architecture., Java, AWS, Google Cloud Platform, Enterprise Architecture, Kubernetes, LLMs, Software Design, Solutioning, Azure Service Bus, Azure AI Search ## Description UST is seeking a senior Enterprise Architect with healthcare payer background to define and lead the architecture of large-scale, mission-critical enterprise systems and bring Generative AI and Agentic AI solutions into the enterprise landscape. The ideal candidate has deep Java or .NET platform expertise, a track record of architecting distributed systems at enterprise scale, and hands-on understanding of LLM-based applications, retrieval-augmented generation (RAG), and autonomous agent frameworks. This role works with business leaders, engineering teams, and security and data governance functions to turn AI capability into governed, secure, and scalable production systems. What You'll Do * Define enterprise reference architectures, target-state designs, and technology roadmaps spanning application, integration, data, and infrastructure layers. * Architect modernization programs, including monolith decomposition, migration to microservices, and cloud-native transformation on Azure, AWS, or GCP. * Lead the design of Generative AI solutions, such as LLM-powered applications, RAG pipelines, vector search, prompt management, and model evaluation frameworks. * Design Agentic AI systems, including multi-agent orchestration, tool and function calling, memory and state management, human-in-the-loop controls, and guardrails. * Establish architecture governance, including design standards, patterns, review boards, and architecture decision records (ADRs). * Evaluate build-versus-buy decisions for AI platforms, model providers, orchestration frameworks, and MLOps/LLMOps tooling. * Ensure security, privacy, compliance, and responsible AI practices are embedded in solution design, including data residency, PII handling, access control, and output monitoring. * Partner with delivery leads, product owners, and client stakeholders to translate business objectives into technical architecture and realistic delivery plans. * Mentor solution architects, tech leads, and engineers, and build internal capability in AI engineering. * Assess and communicate technical risk, cost, and performance trade-offs to executive audiences. This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.