Go-To-Market Lead _AI Product Manager

Role: Go-To-Market Lead AI Product Manager

Location: Minneapolis, MN / Phoenix, AZ

We are seeking a highly technical, product-oriented, and customer-focused individual to drive adoption and delivery of Generative AI and agentic AI capabilities across the enterprise. This individual will function as a blend of:

• Go-To-Market Leader defining and executing adoption strategies for AI platforms and capabilities
• Forward-Deployed Engineer working directly with business teams to prototype, build, and deploy AI-powered solutions in real-world workflows

You will play a critical role in turning emerging AI capabilities into tangible business impact , partnering closely with product, engineering, and line-of-business stakeholders to accelerate experimentation, deployment, and scale.

This role requires a strong bias for action, comfort with ambiguity, and the ability to leverage modern AI-native development tools to move from idea to working solution rapidly.

Responsibilities:

1. Go-To-Market Leadership & Adoption
   1. Define and execute GTM strategies for enterprise AI capabilities, with emphasis on LLMs, agentic systems, and composable AI platforms
   2. Drive adoption of APIs, agent frameworks, orchestration layers, and developer tools through targeted enablement and engagement
   3. Lead feature launches and platform rollouts, translating technical capabilities into clear business value narratives

1. Forward-Deployed Engineering & Solution Acceleration
   1. Partner directly with business and engineering teams to design, prototype, and deploy GenAI and agentic solutions
   2. Build hands-on demos, reference implementations, and rapid prototypes that showcase platform capabilities in real-world use cases
   3. Engage in pair programming, debugging, and solution development, accelerating time from concept to production
   4. Leverage tools such as GitHub Copilot, Devin, Cursor, and other AI-assisted development platforms to rapidly solve problems and iterate

1. Customer Enablement & Developer Experience
   1. Lead workshops, office hours, and hands-on sessions focused on building with LLMs, RAG architecture, and agentic workflows
   2. Develop scalable enablement assets (SDKs, playbooks, reusable components, prompt libraries, agent templates)
   3. Improve developer experience and time-to-value by identifying friction points and driving improvements across tooling and documentation

1. Solution Strategy & Agentic Architecture
   1. Translate business problems into GenAI and agentic solution architectures, incorporating patterns such as RAG, tool use, multi-agent orchestration, and memory frameworks
   2. Partner with platform teams to define reusable design patterns, accelerators, and reference architectures
   3. Stay at the forefront of GenAI, agentic systems, LLMOps, and emerging AI-native development paradigms

1. Feedback Loop & Product Influence
   1. Establish tight feedback loops with end users to shape platform roadmap and prioritize enhancements
   2. Capture insights across deployments to inform improvements in usability, performance, and scalability of AI solutions
   3. Champion a customer-first, experimentation-driven culture across AI initiatives