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Senior Principal Architect Agentic AI & Digital Platforms


Job Location:

Dallas, TX - USA

Monthly Salary: Not provided by the employer
Experience Required: 5years
Posted: 6 October 2026 (19 days ago)
Application Deadline: 3 January 2027
Vacancies: 1 Vacancy

Job Summary

Our client is looking for a Senior Principal Architect Agentic AI & Digital Platforms to serve as the onshore technical anchor for an Agentic AI initiative across customer-facing digital platforms. The ideal candidate will translate business intent into scalable governed production-ready systems and hold the architectural line across delivery teams. The right person codes reviews and debates trade-offs in the same week they brief a VP.


Key Responsibilities:
  • Agentic Architecture - Design & govern end-to-end agentic architecture for apps loyalty payments and commerce workflows.
  • Multi-Agent Orchestration - Orchestrator/subagent hierarchies tool calling stateful graph workflows agent memory layers.
  • MCP Standards - Establish Model Context Protocol standards for governed tool and enterprise service exposure.
  • Runtime Guardrails - Spend controls fraud hooks human-in-the-loop checkpoints and full auditability trails.
  • Retail Systems Integration - Lead AI agent integration with catalog inventory pricing promotions loyalty and checkout.
  • LLMOps Standards - Prompt versioning RAG governance evaluation harnesses observability (latency cost drift safety).

Requirements
Must-have (non-negotiable):
  • 1218 yrs enterprise/platform architecture
  • 34 yrs AI/ML or GenAI in production
  • Shipped LLM-based agent systems (not POC)
  • Hands-on: LangGraph / LangChain / Semantic Kernel / CrewAI / AutoGen
  • ReAct multi-agent hand offs RAG MCP knowledge
  • Architected against hallucination tool misuse cost runaway
  • Python proficiency reference implementations
  • Translates tech business value for VPs
Preferred:
  • Direct retail / commerce domain exposure
  • LLMOps depth (LangSmith / Langfuse)
  • Onshore/offshore delivery leadership
  • Knowledge graphs as grounding layers


Required Skills:

>1218 yrs enterprise/platform architecture 34 yrs AI/ML or GenAI in production Shipped LLM-based agent systems (not POC) Hands-on: LangGraph / LangChain / Semantic Kernel / CrewAI / AutoGen ReAct multi-agent handoffs RAG MCP knowledge Architected against hallucination tool misuse cost runaway Python proficiency reference implementations Translates tech business value for VPs