AI Solution Architect

Key Responsibilities:

• Design and lead production-ready AI/GenAI solutions using Azure OpenAI, RAG, AI Agents, and tool calling.
• Define AI boundaries, evaluation, guardrails, human review, and release processes.
• Own the end-to-end Azure application architecture, from design through production.
• Design scalable application architecture using DDD, Clean/Hexagonal Architecture, Azure SQL, Service Bus, and CI/CD.
• Lead legacy modernization, architecture decisions, code/design reviews, and technical teams.
• Create C4 diagrams and ADRs and communicate architecture, costs, and risks to technical and business stakeholders.

Required Skills:

• Has 12+ years of software engineering experience and 4**+ years as an Architect**.
• Has shipped GenAI/LLM applications to production, specifically RAG or tool-calling agents, structured outputs, and prompt/model versioning.
• Has real experience with AI evaluation and guardrails in production—not just GenAI development.
• Can make sound decisions on where AI should and should not be used, with real project examples.
• Has owned production architecture using Clean/Hexagonal Architecture, DDD, domain boundaries, and Anti-Corruption Layers.
• Is still hands-on/coding with Azure + .NET or Node.js, including Azure SQL, Service Bus, hosting, CI/CD, and IaC.

Additional Experience Desired:

• Experience with multi-tenant SaaS architecture and tenant isolation.
• Experience with legacy modernization, including Strangler Fig, feature flags, and parity validation.
• Experience with Azure AI Document Intelligence and document generation/rendering.
• Exposure to .NET and Node.js, with Python for AI services.
• Experience with third-party integrations such as e-signature, payments, messaging, and data feeds.
• Knowledge of OpenID Connect/SAML, Web Components, and design-token systems.
• Experience with AI cost optimization, including token usage and cost per tenant.
• Azure Solutions Architect Expert or Azure AI Engineer certification.