Enterprise AI Architect: LLMs, Agents & Cloud

Quantum Technologies. LLC; Dallas (TX); On-site; USD 180,000 - 260,000; Full time

Job summary

Quantum Technologies. LLC is seeking an experienced AI Architect to lead enterprise AI initiatives in a leadership capacity. You will translate business problems into agent-driven blueprints and guide executive stakeholders on AI adoption, maturity models, and roadmaps.

You will architect agent systems using enterprise data, APIs, and secure workflows. You will ensure scalability, observability, and cost optimization of AI platforms, while establishing guardrails for safety, bias,

Qualifications

• Deep expertise in LLMs, prompt engineering, and reasoning frameworks.
• Hands-on experience with agentic frameworks, RAG and grounding.
• Strong understanding of cloud-native architectures and deployment patterns.

Responsibilities

• Translate business problems into agentic solution blueprints.
• Partner with executives to identify high‑impact AI use cases.
• Provide guidance on AI adoption, maturity, and roadmaps.
• Architect RAG-based agents using enterprise data, APIs, and workflows.
• Ensure scalability, observability, and cost optimization of AI platforms.
• Establish AI guardrails for safety, bias, explainability, and auditability.
• Collaborate with Risk, Legal, Security, and QE for MRM readiness.
• Drive standards for agent testing, validation, and certification.

Skills

LLMs

Prompt Engineering

Agentic frameworks

Distributed systems

Python

Cloud platforms

PCI/AWS Azure GCP

Tools

LangGraph

AutoGen

CrewAI

Semantic Kernel

Job description

Quantum Technologies. LLC is seeking an experienced AI Architect to lead enterprise AI initiatives in a leadership capacity. You will translate business problems into agent-driven blueprints and guide executive stakeholders on AI adoption, maturity models, and roadmaps.

You will architect agent systems using enterprise data, APIs, and secure workflows. You will ensure scalability, observability, and cost optimization of AI platforms, while establishing guardrails for safety, bias,