AI Engineer - Workforce Reinvention - name

About the Team

Our Workforce Reinvention team is at the forefront of driving efficiency and innovation across OpenSesame . We operate in an agile, continuously improving environment focused on optimizing workflows and empowering internal teams through practical automation and AI-driven solutions.

The team partners closely with non-technical business groups including Sales, Marketing, and Finance to build scalable systems that reduce operational toil and accelerate productivity across the enterprise.

About the Role

The Workforce Reinvention – AI Engineer will help scale modular tools, intelligent workflows, and production-grade Retrieval-Augmented Generation (RAG) systems that support internal business operations. This person will serve as a pragmatic builder who consistently selects the most efficient solution for each challenge, whether through system integrations, lightweight scripting, reusable automation components, or custom AI agents.

The role will focus initially on maturing existing AI proofs-of-concept into reliable production systems while establishing engineering rigor through Test-Driven Development (TDD), CI/CD automation, infrastructure-as-code practices, and operational monitoring.

Success in this role will require strong partnership with internal “AI Champions” across departments to create reusable automation capabilities that empower teams to safely self-serve and scale intelligent workflows across OpenSesame .

Performance Objectives

30 Days — Onboarding, Context, and First Contribution

• Develop a comprehensive understanding of the current Workforce Reinvention architecture, codebase, deployment pipeline, and existing AI proofs-of-concept while building strong working relationships with AI Champions in Sales, Marketing, and Finance.
• Within the first month, successfully contribute and deploy a small but meaningful workflow improvement, automation script, or enhancement to an active internal tool while demonstrating the ability to operate within the team’s TDD and CI/CD practices and release processes.

60 Days — Production Launch & Component Foundations

• Take ownership of deploying a production-grade RAG workflow or intelligent internal tool built from a previously validated concept, ensuring the solution is stable, maintainable, and valuable to internal stakeholders.
• Partner closely with AI Champions to identify and prioritize workflow bottlenecks while beginning to establish reusable modular automation blocks and standardized development patterns that form the foundation of a scalable enterprise component library.

90 Days — Engineering Rigor & Pipeline Optimization

• Lead improvements to the CI/CD pipeline that significantly reduce manual deployment steps, improve release reliability, and accelerate software delivery across automation initiatives.