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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Solution Architect II - **Company:** Pavan Raikhelkar - **Location:** United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Software Applications, Microsoft Azure, Cloud Engineering, Code Review, Information Engineering, Decision Support Systems, DevOps, Design of User Interfaces, Python (Programming Language), Machine Learning, Recommender Systems, Azure Machine Learning, Search Technologies, Software Engineering, Data Streaming, Systems Integration, Enterprise Software Applications, Chatbots, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Spring-boot, Generative AI, Event Driven Architecture, AI Platforms, Information Technology, Data Management, Virtual Agents, Api Design, Legacy Systems, Microservices - **Published:** August 25, 2026 - **Apply:** https://www.dice.com/job-detail/4e23740e-3fdc-4272-9ed6-8de1768664cf ## About the Role Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, Data Science, or a related field. 10+ years of experience in Software Engineering, Solution Architecture, Cloud Architecture, Data Engineering, AI Engineering, Integration, or Enterprise Delivery. 3+ years of experience designing and delivering AI, Machine Learning, Generative AI, Intelligent Automation, or Advanced Analytics solutions. Proven hands-on experience developing agentic AI solutions with tool-using agents, stateful orchestration, approvals, exception management, and recovery workflows. Strong expertise in: Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) Prompt Engineering Structured Outputs Semantic & Vector Search AI Evaluation Frameworks AI Guardrails & Responsible AI Experience architecting OCR/IDP, Conversational AI, Email Intelligence, Classification Engines, Recommendation Systems, and Workflow Automation solutions. Strong knowledge of APIs, Microservices, Event-Driven Architecture, Security, Data Platforms, Observability, and DevOps. Experience with Azure OpenAI, Azure AI Search, Azure AI Services, Azure Storage, Azure Identity, Azure Monitoring, Python, and cloud-native application development. Proven ability to lead distributed engineering teams and collaborate effectively with business and technical stakeholders ## Description The Software Solution Architect II will lead the architecture, design, and delivery of enterprise-scale Agentic AI and Intelligent Automation solutions. This role is responsible for defining end-to-end architecture across AI services, agent orchestration, workflows, document processing, integrations, data platforms, security, observability, DevOps, and cloud-native deployment. The architect will work closely with business and technology stakeholders to translate requirements into scalable, secure, and production-ready solutions., Own end-to-end architecture covering AI services, agent orchestration, workflows, document processing, integrations, data platforms, user interfaces, security, observability, DevOps, and deployments. Translate business and non-functional requirements into solution architectures, data flows, deployment models, integrations, and technical standards. Design and lead hands-on development of tool-using agents using LangGraph or equivalent agent orchestration frameworks. Define agent roles, tools, memory, state management, routing, retries, fallback mechanisms, and workflow termination strategies. Architect multi-agent systems for search, extraction, classification, conversational AI, recommendations, decision support, and workflow automation. Design human-in-the-loop validation, approval workflows, escalations, governance controls, AI guardrails, confidence scoring, and responsible AI patterns. Architect RAG solutions, semantic/vector search, prompt engineering frameworks, structured outputs, AI evaluation methodologies, and OCR/IDP pipelines. Design API-first and event-driven integrations with enterprise applications, document repositories, email systems, external platforms, knowledge bases, and legacy systems. Guide Azure cloud-native solution development using Python, Java/Spring Boot, React, Azure AI services, storage, identity, monitoring, and CI/CD pipelines. 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