Agentic AI Solutions Architect

Veridic Solutions LLC; Dallas (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

Veridic Solutions LLC is seeking a hands-on AI Architect to design and implement scalable, secure, production-ready AI solutions across enterprise digital platforms in Dallas, TX. The role collaborates with business and technical teams to deliver end-to-end AI capabilities, including multi-agent architectures and integration with essential systems.

The ideal candidate brings 12–18 years in enterprise architecture with 3–4+ years in AI/GenAI production, deep Python expertise, and hands-on

Qualifications

• 12–18 years of enterprise architecture experience, including 3–4+ years in AI/ML or GenAI production solutions.
• Hands-on experience with LangGraph, LangChain, Semantic Kernel, CrewAI, or AutoGen.
• Strong Python, API, distributed systems, and event-driven architecture skills.
• Experience with RAG, MCP, prompt engineering, and LLMOps tools.
• Retail, e-commerce, loyalty, payments, or commerce platform experience preferred.

Responsibilities

• Design and implement Agentic AI and multi-agent architectures.
• Develop AI solutions using LLMs, RAG, MCP, and agent frameworks.
• Integrate AI agents with enterprise applications, retail, commerce, and payment systems.
• Establish LLMOps standards for monitoring, evaluation, security, and cost control.
• Lead technical design, Python development, code reviews, and architecture decisions.
• Collaborate with business stakeholders and onshore/offshore delivery teams.

Skills

AI/ML production

Python development

Distributed systems

LLMOps

Tools

LangGraph

LangChain

Semantic Kernel

CrewAI

AutoGen

Job description

We are looking for a hands-on AI Architect with strong experience in Agentic AI, Generative AI, and enterprise digital platforms. The candidate will design and implement scalable, secure, production-ready AI solutions and work closely with business and technical teams.

Key Responsibilities

• Design and implement Agentic AI and multi-agent architectures.
• Develop AI solutions using LLMs, RAG, MCP, and agent frameworks.
• Integrate AI agents with enterprise applications, retail, commerce, and payment systems.
• Establish LLMOps standards for monitoring, evaluation, security, and cost control.
• Lead technical design, Python development, code reviews, and architecture decisions.
• Collaborate with business stakeholders and onshore/offshore delivery teams.

Required Skills

• 12–18 years of enterprise architecture experience, including 3–4+ years in AI/ML or GenAI production solutions.
• Hands-on experience with LangGraph, LangChain, Semantic Kernel, CrewAI, or AutoGen.
• Strong Python, API, distributed systems, and event-driven architecture skills.
• Experience with RAG, MCP, prompt engineering, and LLMOps tools.
• Retail, e-commerce, loyalty, payments, or commerce platform experience preferred.
• Strong communication, technical leadership, and problem-solving skills.