Sr AI Architect

ob Description

Must-Have 

• Experience in enterprise architecture; 3+ years on Gen-AI/AI Architecture, AI governance, Responsible AI, or model-risk programs 
• Experience in GenAI, Agentic AI, Multi-Agent model, LLM ,LangChain, LangGraph, LangSmith, RAG, RAGAS, DeepEvals, Azure AI services
• AI governance frameworks — RBAC design, policy guardrails, audit trail configuration, and model risk concepts
• Hands-on with at least three of: Azure AI Content Safety, Azure Purview, Microsoft Defender for Cloud, Entra ID (RBAC/Conditional Access), Azure Monitor + Log Analytics, Application Insights/OpenTelemetry 
• LLM observability tooling exposure: Azure AI Foundry Evaluations, or equivalent 
• Reliability patterns for multi-step agent workflows: timeouts, retries, circuit breakers, idempotency keys, fallback routes, dead-letter queues 

Good to Have:

• HITL workflow design - approval workflows, escalation logic, and decision checkpoint implementation within agentic pipelines- using Microsoft Teams approvals, Adaptive Cards
• Governance documentation: runbooks, operating guides, and playbooks

Key Responsibilities 

• Defien, Design & Implement GenAI, AgenticAI architecture, workflows
• Design reliability patterns for multi-step agent workflows (timeouts, retries, and fallbacks) and reflect these in architecture  
• Author the governance + HITL operating model: monitoring, logging, bias/drift detection, escalation matrices, audit evidence, and runbooks 
• Define RBAC (Entra ID groups, Snowflake roles), policy guardrails, and ethical safeguards across agentic workflows 
• Drive deliverable acceptance through walkthroughs, dashboards, and traceable evidence within the 10-business-day Acceptance Review Period