Senior AI Architect (Remote)

KSHB / KMCI / The EW Scripps Company•Colorado Springs, MI

17d•Remote

About The Position

The E.W. Scripps Company is seeking a Senior AI Architect to build and deploy AI-powered applications and agent-based systems that address moderately complex to complex business challenges. Work both independently and collaboratively to implement well-engineered AI solutions using modern frameworks, cloud model providers, and tool integration patterns. This role will contribute to the organization's AI platform and agent ecosystem while deepening expertise in applied AI engineering.

Requirements

Solid track record building and shipping software applications, with growing experience in AI/agent systems.
Hands-on experience with at least one agent framework (LangChain, LangGraph, AutoGen, CrewAI, or similar).
Understanding of RAG implementations, vector search, and prompt engineering best practices.
Working knowledge of MCP or equivalent tool-use protocols for LLM integrations.
Experience with at least one major cloud platform's AI/model services (AWS Bedrock, Azure OpenAI, etc.).
Proficiency in Python and/or TypeScript/Node.js for backend AI development.
Familiarity with REST APIs, containerization (Docker), and cloud deployment patterns.
Strong analytical and problem-solving skills with an engineering-first mindset.
Good communication skills and ability to collaborate effectively across teams.
BS/BA in Computer Science, Software Engineering, or related discipline; or equivalent experience required.
Generally 5+ years of experience in software engineering or a related field; applied AI or agent development experience preferred.

Nice To Haves

Experience in the Media and Broadcast domain is a plus.

Responsibilities

Participate in AI solution architecture discussions and contribute hands-on to technical design and implementation.
Develop and deploy AI agents and LLM-integrated applications under minimal supervision, utilizing structured outputs and function/tool calling patterns.
Design and implement RAG (Retrieval-Augmented Generation) architectures, including the integration and management of vector databases.
Set up and configure MCP servers and define tool integrations to extend agent capabilities.
Integrate with cloud model providers (AWS Bedrock, Azure OpenAI, etc.) and assist in evaluating models for specific use cases.
Apply AI evaluation and observability techniques to monitor and improve agent behaviors and application performance.
Apply software engineering best practices — including testing, version control, code review, and documentation — to all AI development work.
Collaborate with cross-functional teams to gather requirements and integrate AI components into production systems.
Support prototyping efforts and contribute to testing and validating agent behaviors and tool integrations.
Contribute to internal documentation, knowledge sharing, and engineering standards for AI development.
Adhere to company standards for AI security, ethics, and responsible use, with a focus on mitigating prompt injection and PII leakage.