AI Enablement Specialist

Overview

Allspring is promoting responsible integration of Generative and Agentic AI across the organization. We are seeking an AI Enablement Specialist, reporting to the Head of AI Product Management, to grow everyday, department-specific AI usage by delivering enablement, developing repeatable workflows, and supporting a vibrant internal community of practice. In this role, you will spend roughly half your time enabling AI proficiency through our AI Champions network—training, office hours, playbooks, and communications—and the other half building and refining practical GenAI and agent-enabled solutions, including workflow creation, prompt packs, lightweight agent prototypes, and evaluation.

This is a junior-level position well suited to someone with strong GenAI skills, a builder's outlook, and the communication and teaching skills to help others succeed.

We currently operate in a hybrid working model, whereby you will be required to work in-office 4 days per week.

Location(s):
Milwaukee, WI

• Collaborate with the AI Champions network and business functions to understand workflows, pain points, and opportunities for Generative and Agentic AI.
• Develop and refine department-specific AI solutions (e.g., copilots, prompt packs, and lightweight agents) that boost performance while meeting security and compliance expectations.
• Build and maintain enablement materials (quick-start guides, office hours content, demos, FAQs, and templates) that help teams build confidence and good habits with AI.
• Facilitate hands-on sessions for Champions and end users (training, workshops, and “build with me” labs) to reinforce responsible prompting and workflow development.
• Develop repeatable playbooks for common patterns (summarization, drafting, analysis, retrieval/grounding, and agentic task flows) and help Champions adapt them to their teams.
• Develop and test GenAI-enabled workflows and lightweight agents (no-code/low-code and/or basic scripting as appropriate), recording assumptions, limitations, and success criteria.
• Test and evaluate AI outputs for accuracy, usefulness, consistency, and policy alignment; build lightweight test sets, capture failure modes, and recommend improvements to prompts, grounding, and workflow/agent design.
• Help build and maintain shared assets (prompt libraries, workflow templates, and standards) to accelerate consistent adoption across departments.
• Partner with appropriate collaborators to move successful pilots into supported solutions (requirements, handoffs, documentation, and ongoing iteration).
• Support Microsoft-centric productivity workflows where applicable (e.g., Copilot experiences and related tooling) and translate capabilities into practical “how to use it” guidance.
• Track adoption signals and feedback and iterate the enablement approach and assets accordingly.
• Stay current on AI and agentic best practices and share practical takeaways with Champions and partners in clear, business-friendly language.

• Bachelor’s degree in Computer Science, Information Science, Business, Analytics, or a related field; equivalent experience may be considered.
• 1-3 years of experience in one or more of the following areas:
  GenAI solution support, building workflows, business process improvement, training, or analytics.
• Practical experience with Generative AI tools and large language models, including iterative prompting, structured outputs, and basic evaluation of output quality.
• Experience with agent patterns and tooling (e.g., tool/function calling concepts, orchestration, RAG/grounding, and basic evaluation approaches), including MCP (Model Context Protocol) for connecting models to tools and data sources.
• Strong communication skills (written and verbal) with the ability to explain AI concepts to non-technical audiences and build clear job aids and documentation.
• Ability to break down business processes into steps, identify where AI solutions may help, and build practical workflows with appropriate guardrails.
• Comfortable designing workflow automations and agentic processes through low-code tools and/or simple scripting; capable of turning concepts into a…