Agentic & Gen AI Go-To-Market Lead

Role : Agentic & Gen AI Go-To-Market Lead Location : Minneapolis, MN / Charlotte, NC / Irving, TX (Hybrid) About this role: seeking a Go-To-Market Lead to join the Digital Technology & Innovation (DTI) organization. DTI supports Corporate Strategy, Digital Platforms & Innovation, working to advance enterprise AI capabilities and accelerate the integration of cutting-edge innovation into customer-facing products and internal platforms. This role sits at the intersection of product, engineering, and go-to-market (GTM) and is designed for a hybrid leader–builder: someone who not only shapes strategy but also gets hands-on building prototypes, coding solutions, and rapidly demonstrating value. 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. In this role, you will: Go-To-Market Leadership & Adoption • Define and execute GTM strategies for enterprise AI capabilities, with emphasis on LLMs, agentic systems, and composable AI platforms • Drive adoption of APIs, agent frameworks, orchestration layers, and developer tools through targeted enablement and engagement • Lead feature launches and platform rollouts, translating technical capabilities into clear business value narratives Forward-Deployed Engineering & Solution Acceleration • Partner directly with business and engineering teams to design, prototype, and deploy GenAI and agentic solutions • Build hands-on demos, reference implementations, and rapid prototypes that showcase platform capabilities in real-world use cases • Engage in pair programming, debugging, and solution development, accelerating time from concept to production • Leverage tools such as GitHub Copilot, Devin, Cursor, and other AI-assisted development platforms to rapidly solve problems and iterate Customer Enablement & Developer Experience • Lead workshops, office hours, and hands-on sessions focused on building with LLMs, RAG architecture, and agentic workflows • Develop scalable enablement assets (SDKs, playbooks, reusable components, prompt libraries, agent templates) • Improve developer experience and time-to-value by identifying friction points and driving improvements across tooling and documentation Solution Strategy & Agentic Architecture • Translate business problems into GenAI and agentic solution architectures, incorporating patterns such as RAG, tool use, multi-agent orchestration, and memory frameworks • Partner with platform teams to define reusable design patterns, accelerators, and reference architectures • Stay at the forefront of GenAI, agentic systems, LLMOps, and emerging AI-native development paradigms Required Qualifications • 4+ years of experience in Artificial Intelligence experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education • 3+ years in go-to-market leadership, technical product, solution engineering, or forward-deployed engineering roles • Hands-on experience building with GenAI/LLMs and agent-based systems, including rapid prototyping and deployment • Strong programming skills and experience working with modern development stacks and APIs • 3+ years of experience with cloud platforms (GCP or Azure) and containerization (Docker, Kubernetes/OpenShift)