Senior AI Architect: Enterprise AI Systems & Tooling

The E.W. Scripps Company; Atlanta (GA); On-site; USD 180,000 - 240,000; Full time

Job summary

The E.W. Scripps Company seeks a Lead AI Architect to design and implement enterprise-scale AI solutions with a strong engineering foundation. You will drive agentic systems, tool ecosystems, and AI platform integration across business domains.

Responsibilities include defining AI solution architectures, integrating with major model providers, ensuring security and observability, and mentoring teams to adopt best practices in AI engineering.

Qualifications

• 8+ years in AI/architecture or related field.
• Production AI app design and deployment experience.
• Experience with agent development and orchestration.
• Familiarity with cloud AI services (AWS/Azure).

Responsibilities

• Define and own AI solution architectures across agentic workflows and multi-model orchestration.
• Lead deployment of RAG architectures and vector database strategies for data retrieval.
• Architect MCP servers and tool schemas for LLM tool-use integrations.
• Drive integration with model providers (AWS Bedrock, Azure OpenAI, etc.) and set standards for model routing.
• Establish AI observability, prompt engineering, and evaluation frameworks.
• Collaborate with engineering, product, and platform teams to deliver integrated AI solutions.
• Ensure scalability, security, and maintainability of architectures.
• Mentor peers and promote best practices in AI engineering.
• Address security and responsible AI standards, including OWASP LLM Top 10.

Skills

AI architecture

Agent frameworks

LangChain/CrewAI

RAG patterns

Vector DBs

MCP servers

Model providers

Python

REST/GraphQL

CI/CD/IaC

Security/compliance

Education

BS/BA in CS or related

Tools

Docker

Kubernetes

LangGraph

AutoGen

Job description

The E.W. Scripps Company seeks a Lead AI Architect to design and implement enterprise-scale AI solutions with a strong engineering foundation. You will drive agentic systems, tool ecosystems, and AI platform integration across business domains.

Responsibilities include defining AI solution architectures, integrating with major model providers, ensuring security and observability, and mentoring teams to adopt best practices in AI engineering.