• Design, build, and maintain full stack product capabilities across backend services, APIs, frontend interfaces, and internal tools that support Wunderkind Advertising. • Implement supply-side product capabilities such as new placements, trigger logic, refresh behavior, and multi-campaign activation rules across onsite, in-app, and adjacent ad surfaces. • Build frontend and backend workflows that support advertiser and publisher use cases, including segmentation controls, placement configuration, campaign setup, and bulk-edit or operational tooling. • Contribute to demand-side integrations and optimization work, including SSP onboarding, OpenRTB request / response handling, auction logic, curation flows, and traffic-shaping or path-optimization capabilities. • Partner closely with product managers, designers, and engineers to translate roadmap items into clear technical designs, scoped milestones, and production-ready implementations. • Develop reporting and observability capabilities that improve visibility into bids, impressions, inventory, advertiser outcomes, and platform health. • Write clean, modular, testable code and uphold strong engineering standards through code reviews, documentation, and thoughtful system design. • Help shape architecture and delivery decisions around latency-sensitive systems, event-driven workflows, privacy-aware data handling, and operational reliability. • Support production readiness by contributing to monitoring, troubleshooting, incident response, and ongoing platform improvements.

• Lead and Build the GTM Engineering Function • Set the technical direction, operating model, and standards for the team • Recruit, develop, and retain GTM Engineers as the function grows • Stay hands on. Ship alongside the team on the highest leverage problems • Define what good looks like for discovery, build quality, and impact measurement • Drive Automation and AI Across Revenue Workflows • Identify where automation and AI can replace manual work, accelerate execution, or unlock new capabilities • Build durable automation patterns using AI agents, integration platforms, scripting, and Salesforce native tooling • Own the standards for how AI gets deployed safely in revenue workflows, in partnership with the AI Council and broader Revenue Technology org • Partner Directly with Revenue Leaders • Build trust with Sales, Marketing, CS, and Operations leaders to surface the right problems and align on priorities • Translate revenue strategy into engineering work, and engineering work into business outcomes • Operate as a credible technical voice in cross functional forums • Ship Practical Solutions with Speed • Lead the team in delivering iterative, measurable improvements • Balance quick wins against larger initiatives that require formal prioritization • Maintain a tight feedback loop between build, validate, and refine • Strengthen the Revenue Technology Operating Model • Partner with Program Management on landing and scaling accelerator programs • Coordinate with Salesforce administration, Revenue Systems (Q2C), and Revenue Tools to ensure GTM Engineering work integrates cleanly with the broader platform • Contribute to roadmap, capacity, and investment decisions across Revenue Technology

• Identify and prioritize automation and AI opportunities across GTM, RevOps, Sales, and Operations teams. • Build and integrate AI-powered tools using LLMs, APIs, and automation platforms. • Work with diverse data types. • Act as an internal AI consultant. • Evaluate and integrate third-party AI tools and services. • Maintain and improve the agent fleet. • Stay current on LLMs, AI tools, and automation trends. • Partner with RevOps leadership to shape the AI/automation roadmap.

• Improving the Wikipedia product experience by fixing bugs and implementing new functionality. • Iterating on new features through collaboration with fellow engineers, product managers, designers, other teams, and community members. • Writing multilingual, accessible, and performant code using Javascript and PHP. • Building on top of the MediaWiki API ecosystem. • Instrumenting components to monitor feature behavior and quality characteristics.