Important Note

This is primarily an enterprise enablement, adoption, governance, and transformation role — NOT a hands-on developer role. Candidates should have strong experience driving platform adoption, stakeholder alignment, governance, change management, and technology transformation rather than focusing primarily on production coding.

Job Summary

We are seeking an AI-Native Engineering Enablement Lead to drive enterprise adoption of AI-native software engineering using the Replit platform.

The ideal candidate will lead adoption strategy, governance, change management, stakeholder engagement, and enablement across engineering and business teams.

Responsibilities

• Drive enterprise-wide adoption of AI-native engineering on the Replit platform.

• Define platform adoption strategy, roadmap, and operating model.

• Build business cases and ROI assessments for AI-assisted modernization.

• Establish governance, security controls, quality standards, and auditability for AI-generated code.

• Define AI-native SDLC standards, development workflows, and reusable engineering practices.

• Partner with Engineering, Product, Architecture, Security, Infrastructure, and business teams.

• Lead stakeholder engagement and executive-level presentations.

• Drive organizational change management and build internal AI champions.

• Conduct discovery workshops and identify high-value AI modernization opportunities.

• Develop and deliver training, enablement programs, playbooks, and best practices.

• Mentor engineering teams through AI-native development adoption.

Required Skills

• 8+ years of experience in technology transformation, consulting, platform enablement, or enterprise adoption.

• Strong experience leading enterprise platform adoption / developer-platform enablement programs.

• Proven experience with adoption, governance, change management, and transformation initiatives.

• Strong stakeholder management skills, including senior/executive leadership.

• Experience with digital transformation, business process analysis, and business-case/ROI development.

• Understanding of enterprise architecture and Agile delivery.

• Strong understanding of SDLC, Git, CI/CD, APIs, microservices, and cloud platforms (AWS/Azure/GCP).

• Experience or familiarity with Replit, GitHub Copilot, Cursor, or similar AI-assisted development tools.

• Knowledge of LLMs, prompt engineering, and agentic AI workflows.

• Understanding of AI governance and Responsible AI, particularly governance of AI-generated code.

Preferred

• Experience in a similar enterprise platform enablement / developer experience role.

• Experience driving large-scale modernization or AI adoption initiatives.

• Life Sciences or other regulated-industry experience.

• Experience with AI-assisted software development platforms.