• 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.

• Lead complete projects independently across backend services, APIs, and data pipelines, defining experimentation, development, and rollout strategies across multiple systems with minimal guidance. • Architect scalable, robust solutions for performance, reliability, and cost efficiency, applying deep technical knowledge to design systems that handle high-throughput marketing operations. • Drive technical improvements by identifying and solving deeper underlying problems, designing appropriate abstractions to simplify complexity and promote reusability across the codebase. • Partner directly with Marketing and Product stakeholders to influence features and requirements, bringing strong technical perspective while making well-reasoned trade-offs between complexity, business value, and delivery timelines. • Mentor junior engineers through code reviews, technical guidance, and onboarding support, while contributing to team productivity through process improvements and automation.