AI Engineer — Workforce Reinvention

About OpenSesame

OpenSesame offers more than training courses—we provide the opportunity for companies to upgrade employee skills and reinvent their workforce in an AI world. With strategic partnerships across 150+ Global 2000 companies, we deliver training programs that help organizations develop the world's most productive and admired workforces. Now we're building what comes next: intelligent, AI-driven solutions that transform how enterprises operate.

About the Workforce Reinvention Team

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

About the Role

As an AI Engineer on the Workforce Reinvention team, you will help scale modular tools, intelligent workflows, and production-grade Retrieval-Augmented Generation (RAG) systems that support internal business operations. You'll 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.

Your focus will initially center 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 requires strong partnership with internal "AI Champions" across departments to create reusable automation capabilities that empower teams to safely self-serve and scale intelligent workflows throughout OpenSesame.

Key Responsibilities

• Design, develop, and deploy production-grade AI and automation systems, including RAG workflows and intelligent internal tools
• Collaborate with internal AI Champions across Sales, Marketing, and Finance to identify workflow bottlenecks and optimization opportunities
• Establish and maintain engineering best practices including Test-Driven Development, CI/CD automation, and infrastructure-as-code
• Build reusable automation components and modular tools that enable self-serve AI capabilities across the organization
• Transform validated AI concepts into stable, maintainable, and operationally sound production systems
• Create comprehensive monitoring and observability solutions for AI-powered workflows
• Document and establish patterns for safe, scalable AI deployment across enterprise teams

Performance Objectives & 90-Day Milestones

30 Days — Onboarding, Context, and First Contribution

• Develop comprehensive understanding of current Workforce Reinvention architecture, codebase, deployment pipeline, and existing AI proofs-of-concept
• Build strong working relationships with AI Champions in Sales, Marketing, and Finance
• Successfully contribute and deploy a meaningful workflow improvement, automation script, or enhancement to an active internal tool within your first month
• Demonstrate capability 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
• Ensure the solution is stable, maintainable, and demonstrably valuable to internal stakeholders
• Partner with AI Champions to identify and prioritize workflow bottlenecks
• Establish foundational reusable components and patterns for future AI automation initiatives

90 Days — Scaling and Operationalization

• Have multiple AI workflows and automation systems operating reliably in production
• Establish clear documentation, runbooks, and best practices for AI system deployment and maintenance
• Demonstrate measurable productivity gains and cost savings from implemented solutions
• Mentor AI Champions on self-serve capabilities and safe expansion of intelligent workflows

What We're Looking For

The ideal candidate brings strong software engineering fundamentals with proven experience building production AI systems. You're comfortable working across the full stack—from LLM integration and RAG architecture to backend APIs, databases, and operational infrastructure. You excel at pragmatic decision-making, choosing the right tool for each challenge rather than defaulting to complexity. Your communication skills enable you to partner effectively with non-technical stakeholders while maintaining technical rigor.

You have hands-on experience with modern development practices including Test-Driven Development, CI/CD pipelines, and infrastructure-as-code. You understand the operational realities of production systems and build observability and monitoring into your solutions from day one.

💰 Compensation not publicly listed. Market estimate for similar roles: from $80K, varying by experience and location.