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AI GTM Manager

Seeq
CompanySeeq
CategoryData & Analytics
LocationUnited States
RemoteRemote
EmploymentFull-time
LevelManager
SalaryNot stated by the employer
Posted24 Jun 2026
Last verified6 Aug 2026
SourceEmployer ATS (workable)
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Description
The AI GTM Manager is responsible for building and leading Seeq’s AI-enabled go-to-market workflow capability. This role is a player-coach role: it combines hands-on work designing and deploying AI GTM workflows with leadership of a small team to scale the function over time. This leader will help Seeq move from isolated AI experiments to a durable, governed, high-value operating capability that improves the speed, quality, and repeatability of go-to-market execution. The role sits at the intersection of marketing, operations, systems, and applied AI, and partners closely with Product Marketing, Industries, Whole Offer Management, Regional Marketing, Partner Marketing, ABX / Campaign Execution, Field Enablement, Marketing Analytics and Infrastructure, Revenue teams, and Product. The ideal candidate brings strong proven experience as an AI GTM Engineer, combined with the ability to manage, coach, and scale a small team while still personally building high-impact workflows. 1. Lead Seeq’s AI GTM Workflow Strategy Define the roadmap for AI-enabled GTM workflows across priority marketing and commercial motions. Identify the highest-value use cases where AI can improve speed, quality, consistency, reuse, and operating leverage. Prioritize shared workflows that can serve multiple teams before investing in narrow one-off solutions. Translate GTM priorities into a practical AI workflow portfolio spanning research, content assembly, launch planning, campaign development, management, and QA, asset reuse, enablement support, and reporting. Help shape the long-term AI-first operating model for Marketing and Industry & Product GTM. 2. Operate as a Hands-On Builder Personally design, build, test, and deploy high-priority AI workflows, especially in the early stages of the function. Act as the senior practitioner for prompt design, retrieval patterns, workflow orchestration, content structuring, automation logic, and quality controls. Build repeatable systems that improve GTM execution across messaging, launches, campaigns, field support, and knowledge access. Work directly in the tools, systems, and content environments needed to make workflows durable and useful in real work. Set the quality bar for workflow usability, reliability, and business impact through direct hands-on contribution. 3. Manage and Develop a Small Team Lead, coach, and develop a small team of AI GTM Engineers as the function scales. Set clear goals, operating rhythms, development priorities, and standards for workflow design and delivery. Balance direct personal contribution with effective delegation so the team scales without losing speed or quality. Help team members strengthen both technical workflow skills and business understanding of GTM use cases. Build a healthy player/coach culture that values practical execution, cross-functional partnership, reuse, and measurable results. 4. Partner Across the GTM System Work closely with Product Marketing, Industry teams, Whole Offer Management, Regional Marketing, Partner Marketing, ABX / Campaign Execution, and Field Enablement to identify workflow bottlenecks and high-leverage opportunities. Partner with the Manager, Marketing Analytics and Infrastructure to align AI workflows with data, tooling, governance, workflow automation, and reporting systems. Evaluate build vs buy options to identify tools and vendors that add high value relative to building internally. Collaborate with Campaign Program Management and GTM leaders to improve planning quality, coordination, and execution visibility. Work to optimize marketing channels and marketing spend through integration, automations, and AI-enabled end-to-end management of campaigns to accelerate speed to market and scale up of GTM motions. Serve as a translator between technical possibilities and GTM execution realities. Help functional leaders embed AI workflows into real operating motions rather than treating them as side exp