Software Solution Architect II

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. Lead architecture reviews, code reviews, technical decision-making, risk assessments, production readiness, observability strategies, and knowledge transfer activities.

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