Enterprise AI Guardrails & GenAI ML Engineer

Quantum Technologies. LLC; Charlotte (NC); On-site; USD 180,000 - 240,000; Full time

Job summary

Quantum Technologies. LLC seeks an AI Guardrails & AI/ML Engineer to design, develop, and deploy scalable AI solutions for enterprise environments.

You will build direct model access with OpenAI, Anthropic, and other providers across cloud and hybrid platforms, while creating APIs, SDKs, guardrails, and observability to productionize AI workloads. The role requires 5+ years in LLMs, GenAI architecture, prompt engineering, and RAG, with a focus on governance, performance optimization, and cost

Qualifications

• Minimum 5+ years of hands-on experience in LLM-based applications and GenAI architecture.
• Extensive experience with large language models (LLMs).
• Proven ability in prompt engineering, retrieval-augmented generation, and scalable AI solutions.

Responsibilities

• Design, develop, and deploy scalable AI solutions for enterprise environments.
• Integrate direct model access with OpenAI, Anthropic, and other providers across cloud and hybrid environments.
• Develop APIs, SDKs, guardrails, observability, and orchestration for production AI workloads.
• Evaluate model releases, optimize performance, latency, and cost.
• Collaborate with architecture, security, risk, and platform engineering to set governance and data protection standards.

Skills

LLM applications

GenAI architecture

Cloud-native engineering

Vendor direct consumption

Prompt engineering

RAG

Agentic workflow

Model evaluation

Technical innovation

Tools

OpenAI API

Anthropic API

Guardrails frameworks

Job description

Quantum Technologies. LLC seeks an AI Guardrails & AI/ML Engineer to design, develop, and deploy scalable AI solutions for enterprise environments.

You will build direct model access with OpenAI, Anthropic, and other providers across cloud and hybrid platforms, while creating APIs, SDKs, guardrails, and observability to productionize AI workloads. The role requires 5+ years in LLMs, GenAI architecture, prompt engineering, and RAG, with a focus on governance, performance optimization, and cost