Management of AI Engineering Enablement Program

• Be responsible for the implementation of AI and automation tools to improve SDLC efficiency, incorporating the use of tools like ChatGPT Enterprise, Gene. AI, Atlassian Intelligence, Test Assist, and others.
• Complete implementation strategies within Business Units and teams for AI-powered SDLC automation initiatives.
• Identify high-friction phases of the SDLC and define automation opportunities using generative AI, LLMs, and internal agents.
• Coordinate multi-functional teams (R&D, IT, DFP, DevEx) to align automation capabilities with BU priorities.

Technical Enablement & Integration Support

• Serve as the technical point of contact for internal integrations using low-code, no-code, or custom solutions.
• Mentor engineering teams and integration engineers on how to connect AI-powered tools into SDLC workflows (e.g., planning, testing, bug triage).

Tool Operationalization & Community Engagement

• Serve as Product Owner for critical AI and automation projects that drive software transformation initiatives.
• Support the development and improvement of playbooks and guidelines for AI-powered developer enablement.

Strategy, Metrics, and Continuous Improvement

• Establish benchmarks and success criteria for automation pilots and scaled deployments (e.g., time saved, bugs caught, quality uplift).
• Conduct retrospectives and feedback loops with technical and business collaborators to improve approach and roadmap.
• Stay ahead of AI trends and propose strategic adjustments.

How You Get Here

Education:

• Bachelor’s degree/ equivalent experience in Computer Science, Engineering, Information Systems, or related technical field.

Experience:

• 5+ years in a role involving platform engineering, software development process improvement, or enterprise technology enablement.
• Familiarity with integrating AI/ML tools or enterprise SaaS solutions in development environments is a strong plus.