GTM Knowledge Engineer

About the role

As our first GTM Knowledge Engineer, you'll sit at the intersection of Revenue Enablement, Revenue Operations, and Information Systems within the Go-to-Market Center of Excellence. In this highly impactful role, you'll build, deploy, and improve the intelligent interfaces, AI agents, and knowledge systems that support our commercial teams and reduce friction across the seller workflow. This role carries a dual mandate. First, you'll create and operationalize GTM agents that automate seller workflows such as meeting prep, POV generation, certification, stakeholder mapping, and ROI modeling. Second, you'll help reduce systemic friction across the quote-to-cash process by translating complex packaging, policy, and process requirements into clear, proactive user-layer guardrails that help teams move faster and more consistently. At Everlaw, our mission is to promote justice by illuminating the truth. Our company culture is open and democratic and we're committed to the professional growth of our team members, offering an annual learning and development stipend and regular check-ins with managers regarding career goals. If you're looking for a place that values passion, integrity, thinking big, and a desire to learn, we'd love to hear from you! Think you're missing some of the skills and are hesitant to apply? We do not believe in the 'perfect' candidate and encourage you to apply if you feel you can bring value to our team. This is a full-time, exempt position based in our Oakland, CA or New York City office with a hybrid work schedule: in office M/W/Th with the option to work from home on Tu/Fr. Getting started We want you to feel like part of the team early on! Our onboarding process will integrate you into the company with informative sessions on our product, policies, processes, and team structure and goals. We're excited for you to learn, grow, and contribute right away! We trust that you'll bring experience and knowledge that will uplift and uplevel the team, but we don't expect you to know everything on Day 1. You'll work to become a product expert, helping you provide industry-leading coaching and training to improve adoption of Everlaw. In your role, you'll... Build Enablement Agents & Agentic Layers (75%) Custom GTM Agent Engineering: Design, code, and ship localized context-aware GTM Agents that solve explicit seller problems: tactical meeting prep, live stakeholder mapping, automatic POV generation, customer champion deck synthesis, and dynamic ROI modeling. Orchestration Layer Architecture: Program and maintain the backend orchestration layers that parse active CRM deal metrics to surface the exact right agent, script, or asset at the millisecond it is needed in a rep's live workflow. Agentic Onboarding & Certification: Collaborate with the Content Lead to Build interactive, automated AI role-play environments and auto-certification frameworks that adapt automatically to a rep's specific role, target region, or individualized execution gaps. In-Call & Co-Selling Assistance: Prototype real-time sales assistance tools and interactive overlays providing active deal guidance and objection handling support directly inside live call environments. Automated Content Maintenance: Work with the rest of the Center of Excellence team, create programmatic integrations and automated pipelines that connect data sources directly into seller interfaces, preserving content freshness and data accuracy automatically. Drive Q2C Automation & Systemic Interface Fluency (25%) Q2C UX Friction Interception: Master the complete front-end layout of the CPQ platform to map and isolate severe click friction, configuration drop-offs, and administrative delays. Build inline agent validation paths that guide reps step-by-step through complicated calculations (e.g., co-termed add-ons, complex proration structures). Front-End Quoting Guardrails: Program proactive data validation scripts and warning triggers that catch item packaging errors or discount threshold violations directly over the user UI, mitigating back-and-forth rework loops with deal desks. Policy-to-Logic Translation: Take abstract, highly complex operational policies and translate them directly into clean, automated rules-of-the-road within user workspaces, using low-overhead interface apps About you Hands-On Engineering Depth: You have at least 4 years of relevant professional experience, including at least 1 year of hands-on experience building and shipping AI agents, conversational interfaces, or enterprise-grade internal applications-not just managing them. Code Literacy: You have some technical proficiency in programming languages (JavaScript, TypeScript, or Python); experience interacting directly with APIs, vector storage setups, and AI application orchestration frameworks (Claude, modern LLM APIs). Usable UX Development: You have a proven background engineering practical, lightweight tools that non-technical users adopt smoothly Commercia

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