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About This Role
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.
WHAT YOU'LL DO:
- 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.
WHAT YOU'LL NEED:
- 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.
WHAT YOU'LL BRING:
- 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.
- Experience in the Media and Broadcast domain is a plus.
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If you are a current Scripps employee, please do not apply on this site. Please access our internal career site at Worklife \> My Info \> View Open Positions at Scripps.
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SCRIPPS’ COMMITMENT TO A CULTURE THAT CREATES CONNECTION:
At Scripps, we are committed to a culture that reflects the audiences and communities we serve. We are intentional about creating an environment where employees, our audiences and other stakeholders feel valued and inspired to reach their full potential and create connections. To successfully deliver on this commitment, we must understand and reflect the values and perspectives those around us embody. That process begins by looking inward to build and celebrate a respectful workplace where everyone feels a sense of belonging and connection. By continuing to cultivate an environment where all employees have a fair chance to succeed, are included, valued, and seen, we will strengthen the connections that drive positive business impact and align with our core purpose.
ABOUT SCRIPPS:
The E.W. Scripps Company (NASDAQ: SSP) is a diversified media company focused on creating connection. As one of the nation’s largest local TV broadcasters, Scripps serves communities with quality, objective local journalism and operates a portfolio of more than 60 stations in 40\+ markets. Scripps reaches households across the U.S. with national news outlet Scripps News and popular entertainment brands ION, ION Plus, ION Mystery, Bounce, Grit and Laff. Scripps is the nation’s largest holder of broadcast spectrum. Scripps Sports serves professional and college sports leagues, conferences and teams with local market depth and national broadcast reach of up to 100% of TV households. Founded in 1878, Scripps is the steward of the Scripps National Spelling Bee and its longtime motto is: “Give light and the people will find their own way.”
As an equal employment opportunity employer, The E.W. Scripps Company and its affiliates do not discriminate in its employment decisions on the basis of race, sex, sexual orientation, transgender status, gender, color, religion, age, genetic information, medical condition, disability, marital status, citizenship or national origin, and military membership or veteran status, or on any other basis which would be in violation of any applicable federal, state or local law. Furthermore, the company will make reasonable accommodations for qualified individuals with known disabilities unless doing so would result in an undue hardship for the company.
Role Details
About This Role
This role sits at the intersection of AI and engineering, building systems that bring machine learning capabilities into production environments. The scope varies by company, but the common thread is applying AI technology to solve real business problems at scale. Most AI roles today require a combination of software engineering fundamentals and domain-specific ML knowledge, with the exact mix depending on the team's maturity and the product they're building.
The AI job market is evolving fast. New role categories emerge as companies figure out what they need to ship AI-powered products. What matters most is the ability to learn quickly, build working systems, and iterate based on real-world performance data. The specific title matters less than the skills you bring and the problems you can solve. Companies are past the experimentation phase and want engineers who can deliver production-quality systems that work reliably at scale.
Across the 26,159 AI roles we're tracking, AI Architect positions make up 1% of the market. At The E. W. Scripps Company, this role fits into their broader AI and engineering organization.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
What the Work Looks Like
Day-to-day work involves a mix of building, debugging, and collaborating. You'll write code, review pull requests, participate in design discussions, and work with cross-functional teams (product, design, data) to define what AI features should do and how they should behave. Expect to spend time on both technical implementation and communication. Most AI teams operate in two-week sprint cycles, with regular demos and retrospectives. The ratio of heads-down coding to meetings and reviews varies by seniority, with senior roles spending more time on architecture decisions and mentorship.
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
Skills Required
Python and cloud platform experience are common requirements. Specific skill needs vary by company and focus area, but familiarity with ML frameworks, data pipelines, and API design covers the basics for most roles. RAG (Retrieval-Augmented Generation), vector databases, and LLM API integration are increasingly standard requirements across role types.
Beyond the core stack, communication skills matter more than many technical candidates realize. The ability to explain AI capabilities and limitations to non-technical stakeholders is a differentiator at every level. Technical writing, documentation, and clear thinking about tradeoffs are underrated skills in AI roles. Experience with evaluation methodology (how to measure whether an AI system is working well) is becoming a core requirement, especially for roles that involve LLM integration.
Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
Compensation Benchmarks
AI Architect roles pay a median of $292,900 based on 108 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
The E. W. Scripps Company AI Hiring
The E. W. Scripps Company has 2 open AI roles right now. They're hiring across AI Architect. Based in Remote, US.
Remote Work Context
Remote AI roles pay a median of $156,000 across 1,221 positions. About 7% of all AI roles offer remote work.
Career Path
Common paths into AI Architect roles include Software Engineer, Data Scientist, Data Analyst.
From here, career progression typically leads toward Senior Engineer, AI Architect, Engineering Manager, Principal Engineer.
Focus on building things that work. A deployed project that solves a real problem is worth more than any certification. Contribute to open-source, build portfolio projects, and invest in fundamentals (software engineering, statistics, systems design) rather than chasing the latest framework. The AI field moves fast, but the engineers who succeed long-term are the ones with strong fundamentals who can adapt to new tools and paradigms as they emerge.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Look for job postings that specify the problems you'll work on, the tech stack, and the team structure. Vague postings that list every AI buzzword are often a sign the company hasn't figured out what they need. Strong postings describe the product context, the team you'd join, and the specific challenges you'd tackle.
AI Hiring Overview
The AI job market has 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 roles).
AI hiring keeps growing across industries. Companies in tech, finance, healthcare, and retail are all building AI teams. The strongest demand is for people who can bridge the gap between AI research and production engineering. The shift toward generative AI has created new role types (LLM Engineer, Prompt Engineer, AI Agent Developer) that didn't exist three years ago, while traditional roles (Data Scientist, ML Engineer) have evolved to incorporate LLM capabilities.
The AI Job Market Today
The AI job market spans 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (2,416) are outnumbered by mid-level (16,247) and senior (5,153) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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