Job Title
AI Architect / Agentic AI Solution Architect
Work Location (State, City and Zip) Dallas, Texas, 75063
Base salary range (Min. & Max. to be mentioned) To be confirmed: minimum $160,000 / maximum $180,000
Experience Range: Suggested: 10+ years in enterprise technology; 5+ years in cloud/AI architecture; production GenAI experience
Must Have Technical/Functional Skills
• Enterprise AI solution architecture on Azure, including Azure AI Foundry / Azure OpenAI, Azure AI Document Intelligence, secure API integration, and production operations.
• Hands-on agentic AI and intelligent document processing: orchestration, OCR/layout extraction, cross-document checks, field-level evidence, and human-in-the-loop review.
• LLM quality engineering: golden datasets, field-level evaluation, prompt/model versioning, confidence calibration, regression testing, release gates, and monitoring.
• Externalized deterministic business rules, governed configuration, audit trail, approval, rollback, and appropriate use of AI ONLY for judgment-based tasks.
• Integration design for Power Automate, APIs, Snowflake reference data, enterprise data stores, middleware, and downstream EDM/MDM and SAP item-setup processes.
• Security, RBAC, Responsible AI, observability, CI/CD, cost and performance optimization; Python-based implementation experience.
Roles & Responsibilities
• Lead target architecture for Projects and reusable design patterns for subsequent item-setup workstreams.
• Review the existing solution and recommend evidence-based stabilization and enhancements to document extraction, validation, business rules, and exception handling.
• Architect the end-to-end flow: supplier email/forms -> extraction -> validation/enrichment -> rules -> confidence and exception routing -> Product Manager approval -> governed downstream handoff.
• Define traceability for every proposed attribute: source evidence, applied rule, transformation rationale, confidence, reviewer action, and approved value.
• Separate deterministic rules from prompts; design business-configurable rules with controlled changes, regression tests, approvals, audit history, and rollback.
• Establish golden datasets, evaluation metrics, regression suites, release thresholds, drift monitoring, and feedback loops for prompts, rules, and models.
• Design secure integration with existing Azure, Power Platform, reference data, API/middleware, and EDM/MDM/SAP processes; validate interface dependencies before committing to writeback.
• Collaborate with Product Managers, enterprise architecture, security, integration, QA, and support teams; produce architecture decisions, diagrams, NFRs, runbooks, and knowledge transfer.
Generic Managerial Skills, If any
• Lead cross-functional architecture discussions and communicate design trade-offs to technical and business stakeholders.
• Mentor engineers; manage dependencies, risks, quality gates, and stakeholder decisions.
• Translate AI capabilities into measurable accuracy, cycle-time, adoption, supportability, and cost outcomes.
Key Words to search in Resume
AI Architect; Agentic AI; GenAI; Azure AI Foundry; Azure OpenAI; Azure AI Document Intelligence; OCR; Intelligent Document Processing; LLM evaluation; golden dataset; human-in-the-loop; explainable AI; business rules engine; Power Automate; Power Platform; Python; APIs; Snowflake; MuleSoft; SAP; MDM; Responsible AI; CI/CD; observability.
