AI Lead

Role: Agentic & GenAI Go-To-Market Lead

Location: Minneapolis, MN & Charlotte, NC/Hybrid

Duration: 12 Months

About this role:

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

Feedback Loop & Product Influence

• Establish tight feedback loops with end users to shape platform roadmap and prioritize

enhancements

• Capture insights across deployments to inform improvements in usability, performance,

and scalability of AI solutions

• Champion a customer-first, experimentation-driven culture across AI initiatives

Stakeholder Engagement & Communication

• Act as a trusted advisor bridging technical depth and business strategy

• Communicate complex AI concepts clearly to both technical and non-technical audiences

• Deliver executive-ready updates highlighting adoption, business impact, and innovation

outcomes

Governance, Security & Responsible AI

• Ensure adherence to responsible AI principles, model governance, data security, and

regulatory requirements

• Collaborate with risk, compliance, and security teams to operationalize safe and

compliant AI deployments

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)

Desired Qualifications

• Deep expertise in Generative AI and agentic architectures, including:

o LLMs, RAG, embeddings, vector search

o Agent frameworks (LangChain, LangGraph, AutoGen, ADK, or similar)

o Tool use, orchestration, and multi-agent systems

• Experience leveraging AI-assisted development tools (e.g., GitHub Copilot, Devin, Cursor)

to accelerate innovation and delivery

• Strong familiarity with LLMOps practices: prompt/version management, evaluation,

observability, guardrails

• Experience building end-to-end AI applications, from prototype to production

• Proven ability to build demos, prototypes, and customer-facing solutions that drive

adoption

• Experience in large-scale enterprise environments, preferably in regulated industries

• Strong communication and stakeholder management skills with ability to influence

senior leaders

• Ability to operate as both a strategic leader and hands-on builder