AI & Automation Delivery Engineer- Hybrid Des Moines, Iowa

AI & Automation Delivery Engineer
- Hybrid Des Moines, Iowa

Job Category
:
Technology

Requisition Number
: AIAUT
001969

• Full-Time
• Hybrid

Showing 1 location

Wellabe is hiring an AI & Automation Delivery Engineer to join our team. This role supports the AI & Automation Center of Excellence by building practical AI and automation solutions, prototypes, pilots, reusable components, and technical accelerators. This role works with business, technology, architecture, data, security, governance, and process improvement partners to deliver solutions that are secure, supportable, measurable, and aligned with enterprise standards.

The role focuses on delivering immediate value while enabling distributed teams to reuse approved patterns and scale AI and automation responsibly.

• Build AI and Automation Solutions
  • Build, configure, test, and refine AI and automation solutions using approved platforms, patterns, workflows, agents, prompts, connectors, integrations, and reusable components.
  • Develop prototypes, pilots, proofs of value, and early production implementations with the AI & Automation Solution Architect, ensuring solutions are usable, secure, scalable, supportable, and aligned with approved designs.
• Develop Prototypes and Pilots
  • Build lighthouse solutions and working examples that demonstrate practical AI and automation use cases and can be showcased, reused, replicated, or extended across the enterprise.
  • Validate feasibility, user experience, integration needs, data dependencies, platform fit, risks, and production readiness through rapid experimentation, documentation, and lessons learned.
• Create Reusable Technical Assets
  • Develop reusable automation patterns, workflow templates, prompt examples, connectors, scripts, configuration guides, sample solutions, and technical accelerators.
  • Contribute to CoE playbooks, implementation guides, checklists, readiness materials, and asset libraries that help teams build faster, reduce duplication, and improve enterprise consistency.
• Deliver AI and Automation Use Cases
  • Partner with business teams, process improvement teams, and product owners to define use case goals, workflow impacts, user needs, success criteria, requirements, technical gaps, and practical implementation plans.
  • Support implementation from intake through design, build, testing, deployment readiness, adoption, measurement, scale, and production handoff.
• Partner on Solution Architecture
  • Partner with the AI & Automation Solution Architect to convert approved patterns into working implementations, validate design assumptions, and provide feedback on complexity, platform limitations, reusable components, security, scalability, and supportability.
  • Contribute to design documentation, technical standards, configuration guidance, implementation playbooks, and repeatable delivery practices.
• Support Responsible AI and Governance
  • Build solutions aligned with enterprise architecture, responsible AI expectations, information security, data protection, governance, approved tools, and review requirements.
  • Identify, document, and help mitigate risks related to data sensitivity, access controls, prompt behavior, model limitations, integrations, controls, monitoring, auditability, and human-in-the-loop review.
• Prepare for Production
  • Prepare solutions for production by documenting ownership, support model, configuration details, data dependencies, monitoring needs, controls, operational procedures, and knowledge transfer materials.
  • Support testing, user acceptance, defect resolution, deployment readiness, pilot-to-production transition, and continuous improvement based on feedback, usage data, performance results, and lessons learned.
• Enable Distributed Teams
  • Provide hands-on technical support, coaching, demos, examples, office hours, learning sessions, and community support to help teams adopt approved AI and automation patterns and platforms.
  • Help teams select appropriate solution approaches while reinforcing a federated delivery model that builds capability and reduces dependency on the CoE.
• Track Delivery Value
  • Track progress, risks, dependencies, reusable assets, implemented automations, lessons learned,…