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Veridic Solutions · Dallas, TX

AI Architect

Hybridseniorfull timePosted 4 days ago
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Stack mentioned

agentic-airagobservabilityartificial-intelligencegenerative-aisystem-designllmlangchainreactprompt-engineeringapache-kafkadata-governancepython

Role: Senior Principal Architect – Agentic AI & Digital Platforms

Location: Dallas, TX – Onsite

Job Type: Full-Time

🔹 About the Role

We are looking for a Senior Principal Architect – Agentic AI & Digital Platforms to serve as the onshore technical leader for a high-impact Agentic AI initiative focused on customer-facing digital platforms.

This is a hands-on techno-functional architecture role—not a research position and not purely strategic. You’ll translate business objectives into scalable, governed, production-ready AI solutions while providing architectural leadership across multiple delivery teams.

The ideal candidate can design architectures, write code, review implementations, make critical technology trade-offs, and communicate effectively with executive leadership.

🔹 What You’ll Do

- Design and govern end-to-end Agentic AI architectures across digital experiences, including apps, loyalty, payments, and commerce.

- Architect multi-agent orchestration using orchestrator/subagent models, tool/function calling, stateful workflows, and agent memory.

- Establish MCP (Model Context Protocol) standards for secure and governed access to enterprise tools and services.

- Define runtime guardrails covering cost controls, fraud detection, human-in-the-loop workflows, safety, and auditability.

- Lead integration of AI agents with retail systems such as catalog, inventory, pricing, promotions, loyalty, and checkout.

- Establish LLMOps standards for prompt versioning, RAG governance, evaluations, monitoring, and observability.

- Monitor and optimize latency, token consumption, model performance, drift, and safety.

- Act as the primary technical bridge between business executives, engineering teams, architecture teams, and technology partners.

🔹 Required Qualifications

Enterprise Architecture

- 12–18 years of experience in enterprise/platform architecture.

- 3–4+ years of hands-on experience delivering AI/ML or Generative AI solutions in production.

- Strong expertise in API-first architecture, distributed systems, event-driven architecture, real-time data, and scalable applications.

Agentic AI – Must Have

- Proven production experience building and deploying LLM-based agent systems—not just prototypes or POCs.

- Hands-on experience with one or more agent frameworks such as:

- LangGraph

- LangChain

- Semantic Kernel

- CrewAI

- AutoGen

- Strong understanding of ReAct, plan-and-execute patterns, multi-agent handoffs, RAG, context engineering, prompt engineering, and MCP.

- Experience designing RAG pipelines involving chunking, hybrid retrieval, reranking, and grounding.

- Understanding of common agent failure modes, including hallucinations, tool misuse, runaway costs, and infinite loops, with the ability to architect effective controls.

- Experience with LLMOps, including evaluation frameworks, observability tools such as LangSmith/Langfuse or equivalent, and prompt/model lifecycle management.

🔹 Retail & Commerce Experience

- Strong exposure to retail or consumer commerce platforms.

- Experience with catalog, pricing, promotions, loyalty, checkout, payments, or related commerce systems is highly preferred.

- Adjacent e-commerce or consumer technology experience will also be considered.

🔹 Data & Integration

- Strong understanding of event-driven architectures, including Kafka or equivalent technologies.

- Comfortable working with enterprise-scale data quality and integration challenges.

- Experience with semantic models or knowledge graphs for AI/agent grounding is a plus.

🔹 Leadership & Communication

- Ability to translate complex Agentic AI concepts into clear business value for senior executives.

- Strong architectural judgment with the ability to establish boundaries, make trade-offs, and defend technical decisions.

- Experience leading teams across onshore/offshore delivery models.

- Hands-on technical mindset with the ability to develop reference implementations and conduct code reviews.

- Strong Python proficiency expected.

- Comfortable working in a rapidly evolving AI landscape where technologies and standards continue to change.

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