Enterprise AI Architect — LLMs, Agents & Scalable Systems

Valiant Technologies LLC; Dallas (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Valiant Technologies LLC is seeking an experienced AI Architect to lead business and stakeholder alignment for enterprise AI initiatives. You will design agent-driven solutions, guide RAG-based architectures, and collaborate with risk, security, and QE teams to ensure governance and scalability across cloud platforms.

Strong expertise in LLMs, prompt engineering, and enterprise data integration is essential.

Qualifications

• Deep knowledge of LLMs and prompt engineering.
• Experience with agent frameworks (LangGraph, AutoGen, CrewAI, Semantic Kernel, or similar).
• Understanding of RAG, embeddings, vector databases, and knowledge grounding.
• Experience with fine-tuning techniques (LoRA/QLoRA) and evaluation strategies.

Responsibilities

• Translate business problems into agent‑driven solution blueprints.
• Partner with senior stakeholders to identify high‑impact use cases (automation, decision support, quality, operations).
• Provide executive‑level guidance on agentic AI adoption, maturity models, and roadmaps.
• Support client conversations, RFPs, solution pitches, and thought leadership.
• Architect RAG‑based and tool‑augmented agents using enterprise data sources, APIs, and workflows.
• Ensure scalability, resilience, observability, and cost optimization of agent platforms.
• Establish AI guardrails covering safety, bias, explainability, auditability, and regulatory compliance.
• Partner with Risk, Legal, Security, and QE teams to ensure model risk management (MRM) and enterprise readiness.
• Drive standards for agent testing, validation, and certification (functional, non‑functional, and ethical).

Job description

Valiant Technologies LLC is seeking an experienced AI Architect to lead business and stakeholder alignment for enterprise AI initiatives. You will design agent-driven solutions, guide RAG-based architectures, and collaborate with risk, security, and QE teams to ensure governance and scalability across cloud platforms.

Strong expertise in LLMs, prompt engineering, and enterprise data integration is essential.