Responsibilities:

• Define the overall agent architecture: how agents are structured, how they access data, how they are governed, and how the architecture scales as new data domains and use cases come online
• Design and own the central agent integration layer that mediates all data access between agents and the platform, so that guardrails and controls are enforced in one place and consistently applied across all agents built on the architecture
• Evaluate and select LLM frameworks and orchestration approaches, including Databricks Mosaic AI and other platforms, matching technology choices to use case requirements rather than defaulting to a single stack
• Establish the patterns governing how agents interact with governed data, ensuring agents operate within access controls, return accurate and trustworthy answers, and handle business context correctly
• Define guardrails across the agent layer: read-only data access, user- and role-based data access controls, PII handling, output validation, and hallucination mitigation
• Design the agent evaluation framework, including synthetic query suites, accuracy validation, and the use of agents to generate and run test variations against domain coverage and answer consistency, establishing the criteria that determine when an agent is production-ready
• Define user-facing agent experience patterns: conversational vs single-query, output formats, how agents surface caveats and supporting data, and how they are accessed by different user types
• Work with data and analytics teams to ensure the underlying data layer (schemas, metadata, metric definitions) is structured to support accurate agent responses
• Ensure agent architecture respects multi-tenant data boundaries as the platform scales to support additional broadcast partners
• Stay current on the rapidly evolving AI and agent tooling landscape and bring relevant developments into the architecture proactively
• Guide and set standards for the AI developers building agents across the platform, ensuring individual agent work builds consistently on the central architecture.

Qualifications:

• Deep experience designing and deploying production AI agent systems, including LLM selection, orchestration, and evaluation
• Familiarity with Databricks platform and related products
• Strong understanding of how agents interact with structured data, including retrieval patterns, semantic layers, and metadata-driven context
• Familiarity with major LLM platforms and orchestration frameworks, with the ability to evaluate tradeoffs objectively across vendors
• Experience designing safety and governance patterns for AI systems
• Comfortable working across data engineering, analytics, and business stakeholder teams
• Experience in media, advertising, or other data-intensive industries with complex business metrics and multi-system data environments helpful

The salary range for this position is $120-140K.

Nexstar offers full-time employees a comprehensive benefits package to include medical, life and short-term disability insurance, worker’s compensation, and unemployment insurance, 401(k) retirement plan, paid holidays, paid vacation, paid sick time, employee assistance program, bereavement leave, jury duty service time off, military leave, and medical/maternity & family leave.

Nexstar is committed to attracting, developing, and retaining the industry’s top talent. In compliance with the provisions of all applicable state and federal civil rights laws, every effort will be made to employ the most qualified individuals without regard to race, color, religion, disability, age, sex, national origin, citizenship, veteran’s status, sexual orientation, military status, or any other protected personal characteristics.