Enterprise LLM & AI Enablement Lead
Eightelevengroup, Baltimore, Maryland, United States, 21276
Enterprise LLM & AI Enablement Lead
Remote, Maryland
ABOUT THE ROLE We are seeking a collaborative and user‑focused Enterprise LLM & AI Enablement Lead to drive the adoption and responsible use of generative AI tools across the organization. Reporting to the Director, Enterprise AI, this senior individual contributor will focus on end‑user enablement, supporting the rollout of LLM applications, copilots, coding assistants, prompt frameworks, reusable templates, and providing hands‑on advisory support. Unlike AI Platform Engineering—which owns infrastructure, model hosting, and MLOps foundations—this role operates at the application and enablement layer, shaping the tools, experiences, training, and frameworks that democratize AI for business users, analysts, and developers. You will help build the enterprise ecosystem of LLM tools, steward prompt design patterns, support RAG and agent use cases (leveraging backend capabilities provided by Platform Engineering), and grow a strong internal community of practice.
WHAT YOU'LL DO
Design and enhance enterprise‑facing LLM gateways and prompt management experiences in collaboration with AI Platform Engineering.
Develop and maintain front‑end frameworks and patterns for prompting, agent orchestration, RAG‑based application design, and lightweight prototyping.
Create and contribute reusable standards, templates, and UX patterns for consistent and responsible LLM‑powered user experiences.
Partner with Platform Engineering to ensure effective use of compute, vector stores, and model‑hosting services for LLM use cases.
Assist with deployment, adoption, and ongoing optimization of Copilot and other enterprise LLM productivity tools.
Build user‑friendly templates, prompt libraries, reference examples, and starter kits to accelerate solution creation.
Define and maintain citizen‑development guardrails for safe LLM usage without requiring deep engineering expertise.
Collaborate with governance teams to align tools, templates, and workflows with Responsible AI and compliance standards.
Run or support training programs, office hours, workshops, and enablement sessions that teach effective LLM workflows and application patterns.
Build and grow the enterprise Generative AI Community of Practice across developers, analysts, and business users.
Develop playbooks, learning paths, prompt engineering guides, use case patterns, and self‑service documentation.
Provide hands‑on internal consulting to teams using enterprise LLM tools, advising on prompt design, workflow design, and prototype development.
WHAT YOU BRING
4–6+ years of experience in AI/ML, product enablement, application development, or related fields.
Strong understanding of LLM concepts such as prompting, embeddings, RAG architectures, and agent design—focused on application‑layer patterns, not infrastructure.
Experience deploying or enabling enterprise LLM or Copilot tools and driving adoption across diverse user groups.
Demonstrated ability to train, coach, and support end‑users and lightweight/citizen developers.
Excellent communication, facilitation, and community‑building skills.
Experience enabling low‑code/no‑code or citizen‑developer communities (preferred).
Familiarity with organizational change management or digital adoption initiatives (preferred).
Understanding of Responsible AI principles and enterprise compliance requirements (preferred).
Experience partnering with platform engineering teams on tool integration or application workflows (preferred).
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Remote, Maryland
ABOUT THE ROLE We are seeking a collaborative and user‑focused Enterprise LLM & AI Enablement Lead to drive the adoption and responsible use of generative AI tools across the organization. Reporting to the Director, Enterprise AI, this senior individual contributor will focus on end‑user enablement, supporting the rollout of LLM applications, copilots, coding assistants, prompt frameworks, reusable templates, and providing hands‑on advisory support. Unlike AI Platform Engineering—which owns infrastructure, model hosting, and MLOps foundations—this role operates at the application and enablement layer, shaping the tools, experiences, training, and frameworks that democratize AI for business users, analysts, and developers. You will help build the enterprise ecosystem of LLM tools, steward prompt design patterns, support RAG and agent use cases (leveraging backend capabilities provided by Platform Engineering), and grow a strong internal community of practice.
WHAT YOU'LL DO
Design and enhance enterprise‑facing LLM gateways and prompt management experiences in collaboration with AI Platform Engineering.
Develop and maintain front‑end frameworks and patterns for prompting, agent orchestration, RAG‑based application design, and lightweight prototyping.
Create and contribute reusable standards, templates, and UX patterns for consistent and responsible LLM‑powered user experiences.
Partner with Platform Engineering to ensure effective use of compute, vector stores, and model‑hosting services for LLM use cases.
Assist with deployment, adoption, and ongoing optimization of Copilot and other enterprise LLM productivity tools.
Build user‑friendly templates, prompt libraries, reference examples, and starter kits to accelerate solution creation.
Define and maintain citizen‑development guardrails for safe LLM usage without requiring deep engineering expertise.
Collaborate with governance teams to align tools, templates, and workflows with Responsible AI and compliance standards.
Run or support training programs, office hours, workshops, and enablement sessions that teach effective LLM workflows and application patterns.
Build and grow the enterprise Generative AI Community of Practice across developers, analysts, and business users.
Develop playbooks, learning paths, prompt engineering guides, use case patterns, and self‑service documentation.
Provide hands‑on internal consulting to teams using enterprise LLM tools, advising on prompt design, workflow design, and prototype development.
WHAT YOU BRING
4–6+ years of experience in AI/ML, product enablement, application development, or related fields.
Strong understanding of LLM concepts such as prompting, embeddings, RAG architectures, and agent design—focused on application‑layer patterns, not infrastructure.
Experience deploying or enabling enterprise LLM or Copilot tools and driving adoption across diverse user groups.
Demonstrated ability to train, coach, and support end‑users and lightweight/citizen developers.
Excellent communication, facilitation, and community‑building skills.
Experience enabling low‑code/no‑code or citizen‑developer communities (preferred).
Familiarity with organizational change management or digital adoption initiatives (preferred).
Understanding of Responsible AI principles and enterprise compliance requirements (preferred).
Experience partnering with platform engineering teams on tool integration or application workflows (preferred).
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