Job Title: Software Solution Architect II Agentic AI & Intelligent Automation
Location: Remote (US)
Role Summary
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.
Key Responsibilities
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.
Required Qualifications
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