AI Solutions Architect

The Requirements

• Cloud & Infrastructure architecture
• 7+ years of solution or cloud architecture experience; strong preference for Azure (AKS, Azure OpenAI Service, Azure AI Foundry, Azure Functions, API Management, Service Bus, Azure AI Search, Cosmos DB, Azure Data Factory). Equivalent GCP or AWS considered.
• Demonstrated experience designing cloud-native, enterprise-scale applications.
• Familiarity with Well-Architected Framework principles (reliability, security, cost optimization, operational excellence).
• AI, ML & agentic systems
• Proven hands-on experience designing and deploying production RAG systems. Deep knowledge of advanced RAG patterns: hybrid search, re-ranking, contextual chunking, graphRAG, and long-context strategies. Understanding of MCP (Model Context Protocol) as an emerging integration pattern.
• Hands-on experience with LangChain, LangGraph, and agentic orchestration patterns (ReAct, Plan-and-Execute, multi-agent supervisor patterns).
• Experience working with LLM providers: Azure OpenAI, Google Gemini, and open-weight models via Azure AI Foundry model catalogue.
• Familiarity with AI safety, responsible AI principles, and enterprise guardrail patterns (content filtering, grounding checks). Experience designing AI evaluation frameworks (ragas, offline evals, online monitoring, LLM-as-judge).
• Nice to have: Experience designing or advising on predictive ML models (classification, forecasting) — not necessarily model training, but understanding the architecture around data pipelines, feature stores, and model serving in an enterprise context.
• Low-code, automation & platform tools
• Architecture-level knowledge of the Microsoft Power Platform: Power Apps, Power Automate, Copilot Studio (formerly PVA), and AI Builder.
• Exposure to enterprise third-party AI platforms such as Lyzr (agent builder), Moveworks (enterprise AI assistant), or comparable (ServiceNow AI, Glean, Workato). Ability to assess fit-for-purpose versus build vs. buy for AI automation scenarios.
• Backend, integration & software architecture
• Hands-on experience designing backend services in Python and/or Node.js/.NET.
• Familiarity with enterprise application integration: M365 ecosystem (SharePoint, Teams), identity & security (Entra ID, OAuth 2.0, managed identity), and data platforms (Azure Data Lake, Fabric, Purview) as AI data sources.
• Communication & ways of working
• Exceptional ability to communicate complex technical concepts to non-technical senior stakeholders.
• Collaborative mindset with experience guiding and mentoring engineering teams