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
Job source
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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