AI Engineering Lead—Adoption and Excellence

Opus-posted 4 months ago

Full-time • Mid Level

Tucson, AZ

1,001-5,000 employees

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The AI Engineering Lead—Adoption and Excellence will drive our organization's transformation into an AI-augmented engineering powerhouse. This role will shape how our 40+ engineers leverage AI to modernize legacy systems, accelerate development, and deliver breakthrough innovations.

Execute sprint-based rapid interventions to transform critical but neglected codebases.
Deploy for rapid engagements where product management identifies high-impact opportunities.
Create hand-off packages that enable seamless transitions to responsible teams, including architecture diagrams, test suites, and AI-ready documentation.
Serve as an 'AI pair programmer' trainer for critical modernization initiatives.
Transform undocumented legacy code into maintainable, AI-ready codebases with 90%+ test coverage.
Identify opportunities for ML/AI enhancement across products and processes.
Evaluate and prototype AI-powered features such as fraud detection and automated validation systems, intelligent reporting and analytics dashboards, and automating compliance reporting with NLP-based document analysis.
Own company-wide AI models, platforms, and tools inventory.
Develop AI capabilities for customer engagement, analytics, and operational excellence.
Stay current on emerging AI technologies and translate them into practical use cases.
Partner with leadership to define long-term AI strategy and roadmap.
Develop AI usage guidelines balancing innovation with compliance.
Lead cultural transformation initiatives across engineering teams.
Create role-specific training materials for different engineering disciplines.
Build and maintain a library of prompts, templates, and best practices.
Establish and coordinate an AI Champions network across all teams.
Own and expand AI Office Hours program with participation and adoption metrics.
Facilitate hands-on workshops and training programs.
Work with managers to integrate AI into sprint planning and workflows.
Convert AI skeptics through 1-on-1 sessions showing personalized productivity gains.
Create 'safe failure' environments where engineers can experiment without judgment.
Document and address common concerns (job security, code quality, learning curve).
Design engagement initiatives including challenges, contests, and gamified learning platforms.
Create success stories and showcase wins.
Report qualitative and quantitative impact metrics.

3+ years of software development in C#/.NET or similar enterprise environments.
Active daily user of AI development tools with demonstrated productivity gains.
Strong communication skills to influence technical and non-technical stakeholders.
Experience with Git/Azure DevOps and modern development practices.
Proven ability to learn quickly and adapt to emerging technologies.

Proven teaching, mentoring, or technical training experience preferred.
Natural ability to inspire and motivate peers preferred.
Track record of driving adoption of new technologies or processes preferred.
Change management experience or certification preferred.

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