Senior Principal Architect Agentic AI & Digital Platforms

HDJ & Associates INC
Dallas, TX, United States
7 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Working hours
Regular working hours

Tech stack

LangGraph Framework Artificial Intelligence Graph Database Python (Programming Language) Management of Software Versions Web Platforms ReactJS Retrieval-Augmented Generation Large Language Models Multi-Agent Systems Hallucination Detection Langfuse β€” LLM Observability and Analytics Platform
+9 more
Agentic-AI LangSmith CrewAI AutoGen Machine Learning Operations Virtual Agents Model Context Protocol Semantic Kernel Human in the Loop

Job description

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., * 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

  • 12-18 yrs enterprise/platform architecture
  • 3-4+ 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

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