Director, Automation Engineering

NBCUniversal Advertising Products & Solutions (AP&S) is responsible for the product development and project management of NBCUniversal’s full advertising technology suite. From sales support to campaign execution, delivery, and billing, our division services both internal and external customers in support of NBCUniversal’s $7B+ annual advertising business. Together, we’re building the platform that powers the future of advertising at NBCU. We are seeking a Director, Automation Engineering to join the Engineering & Operations team. Reporting to the Sr. Director of Engineering & Operations, this role will build AI-enabled automation systems and production-grade software that support NBCUniversal's data collaboration ecosystem. The ideal candidate is a strong engineering leader who can set technical direction, deliver reliable systems, repeatable workflows, and AI agents that automate complex engineering and operational tasks across data platforms for audience activation, measurement, and reporting. Responsibilities: AI Agent & Automation Engineering Lead the design and delivery of internal AI agents and automation workflows using technologies such as Snowflake Cortex, LangChain, LangGraph or similar frameworks, to support planning, tool use, retrieval, validation, and human-in-the-loop execution where appropriate. Guide the development of reusable tools, APIs, and components that engineers can compose into new agentic workflows. Direct retrieval-augmented generation workflows, context management strategies, and prompt patterns that improve accuracy, reliability, latency, and cost efficiency. Agent Evaluation & Reliability Establish evaluation harnesses, regression tests, and monitoring patterns for AI-agent behavior. Define and hold the team accountable to metrics such as task completion, groundedness, response accuracy, latency, cost, and failure rate. Set guardrails and validation patterns to reduce hallucinations, unsafe outputs, and unreliable automation behavior. Partner with engineering and operations teams to move AI workflows from prototype to production-ready systems. Software Engineering & Platform Development Oversee the design, build, and maintenance of production-grade Python applications, libraries, and services. Champion object-oriented design principles, including encapsulation, abstraction, inheritance/composition, reusable interfaces, and clean separation of concerns to improve maintainability and extensibility. Champion software engineering best practices including modular design, automated testing, CI/CD, code reviews, observability, and documentation. Drive reusable engineering patterns that reduce bespoke development effort and improve consistency across partner engagements. Collaborate with product, engineering, operations, and data platform teams to translate repeatable business needs into scalable technical solutions. Audience & Measurement Productization Lead the development of reusable Python libraries that support clean room capabilities across first-party audience workflows and core measurement use cases, including audience onboarding, ingestion, indexing, activation, campaign and impression delivery analysis, reach and frequency, attribution, and incrementality. Abstract complex analytical and data collaboration workflows into repeatable, self-service components for internal teams and external partners. Enable configurable feature deployment so new audience and measurement capabilities can be delivered quickly and consistently across partners. Team Leadership & Technical Mentorship Hire, develop, and retain a high-performing team of software and AI engineers. Mentor engineers through code reviews, technical design discussions, and operational best practices. Help establish engineering standards for AI-assisted workflows, agentic system design, reusable libraries, and production automation. Promote a culture of reliability, maintainability, and continuous improvement.