Head of Agentic Technologies

The IAB Tech Lab is seeking a visionary and technically rigorous Head of Agentic Technologies
. As the digital advertising ecosystem evolves to incorporate AI agents, systems capable of semi-autonomous and autonomous decision-making and execution, the need for interoperable standards supporting agentic media workflows is paramount.

This leadership role focuses on the strategic development and delivery of the Tech Lab Agentic Roadmap
. The candidate will be responsible for defining the development of new Tech Lab Agentic Ad Management Protocols (AAMP) built on underlying Tech Lab standards to enable AI agents to interact in newly developing agentic workflows on their own and to interface with the existing programmatic ecosystem to ensure transparency, security, and efficiency. This position requires a blend of open-source stewardship, technical specification drafting, and global industry evangelism.

• Roadmap Strategy & Execution: Develop and lead the end-to-end lifecycle of the IAB Tech Lab Agentic roadmap, ensuring milestones align with the evolving needs of brands, agencies, media companies, and their technology partners.
• Standards Harmonization & Integration: Audit and update existing IAB Tech Lab standards to ensure compatibility with rapidly developing agentic use cases. Ensure that agentic workflows are built on Tech Lab foundational standards, and that those underlying standards evolve as needed to support agentic workflows.
• Task Force Management: Lead several Tech Lab Agentic Task Forces, facilitating technical debates and driving consensus among member companies to move agentic specifications and open source frameworks from draft to "Final" status.
• Evangelism &
  
  Education:
  
  Serve as the primary subject matter expert to educate the market, driving global adoption of Tech Lab agentic releases through 1:1 discussions with agencies, brands, and media companies, industry webinars, and industry presentations.

• Advertising Lifecycle Knowledge: A fundamental understanding of how advertising is planned, purchased, and measured. This includes:
• Media Planning Logic: Insight into how advertising campaigns are planned, how budgets are allocated, and how agentic "negotiation" must respect brand safety, pacing and frequency capping, and campaign objectives.
• Advertising Supply Chain: Understanding the roles of the Advertiser, Agency, and Publisher, and how agents can automate the media discovery, planning, and buying hand-offs between these entities.
• Buying Models: Familiarity with various media buying models, as well as understanding the distinction between “Deals”, "Guaranteed" vs. "Open Marketplace" buying.
• Campaign Analytics & Financial Governance: Knowledge of end-to-end campaign performance reporting, discrepancy resolution, and billing reconciliation.

• Modern Integration Patterns: Hands-on experience with:
• Model Context Protocol (MCP): Implementing MCP to enable seamless integration between LLMs and external data sources or tools.
• Agent-to-Agent (A2A): Implementing A2A communication protocols, focusing on negotiation, state management, and hand-off logic.
• Interface Proficiency: Advanced knowledge of REST APIs and Command Line Interfaces (CLIs) is a significant advantage.
• AdTech Infrastructure: Fundamental technical understanding of major ad servers, creative servers, SSPs, and DSPs is a huge plus.
• Core Technical Understanding: Solid technical understanding of Large Language Model (LLM) architecture, including inference mechanics, context window management, basic knowledge of vector embeddings, and structured tool-calling (JSON).
• Integrity & Security Architectures: Proficiency in leveraging deterministic standards and object models to provide the semantic foundation required to mitigate LLM hallucinations and prevent errors within autonomous agentic workflows.
• RAG Framework Knowledge: Practical understanding of Retrieval-Augmented Generation (RAG) techniques to enhance LLM performance by integrating external data sources, specifically to improve accuracy and grounding in agentic decision‑making.